Advertisement
| flatiron data science bootcamp: Build a Career in Data Science Emily Robinson, Jacqueline Nolis, 2020-03-24 Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder |
| flatiron data science bootcamp: Data Science Careers, Training, and Hiring Renata Rawlings-Goss, 2019-08-02 This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build. |
| flatiron data science bootcamp: Deep Learning for Natural Language Processing Stephan Raaijmakers, 2022-12-20 Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Inside Deep Learning for Natural Language Processing you’ll find a wealth of NLP insights, including: An overview of NLP and deep learning One-hot text representations Word embeddings Models for textual similarity Sequential NLP Semantic role labeling Deep memory-based NLP Linguistic structure Hyperparameters for deep NLP Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve human levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. About the technology Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. About the book Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You’ll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses! What's inside Improve question answering with sequential NLP Boost performance with linguistic multitask learning Accurately interpret linguistic structure Master multiple word embedding techniques About the reader For readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required. About the author Stephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO). Table of Contents PART 1 INTRODUCTION 1 Deep learning for NLP 2 Deep learning and language: The basics 3 Text embeddings PART 2 DEEP NLP 4 Textual similarity 5 Sequential NLP 6 Episodic memory for NLP PART 3 ADVANCED TOPICS 7 Attention 8 Multitask learning 9 Transformers 10 Applications of Transformers: Hands-on with BERT |
| flatiron data science bootcamp: Neural Network Projects with Python James Loy, 2019-02-28 Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key FeaturesDiscover neural network architectures (like CNN and LSTM) that are driving recent advancements in AIBuild expert neural networks in Python using popular libraries such as KerasIncludes projects such as object detection, face identification, sentiment analysis, and moreBook Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learnLearn various neural network architectures and its advancements in AIMaster deep learning in Python by building and training neural networkMaster neural networks for regression and classificationDiscover convolutional neural networks for image recognitionLearn sentiment analysis on textual data using Long Short-Term MemoryBuild and train a highly accurate facial recognition security systemWho this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks. |
| flatiron data science bootcamp: How to Make Your PhD Work Thomas R. Coughlin, 2023-10-11 How to Make Your PhD Work A modern guide for a challenging modern PhD market The job market for PhDs in science and engineering has become immensely more challenging in the last decade. As of 2022, less than 5% of PhDs attain permanent academic positions, yet books about navigating PhD programs continue to treat permanent academic employment as the assumed norm. Today’s PhDs need tools not only for completing their programs successfully, but for positioning themselves in a varied and competitive job market. How to Make Your PhD Work meets this need, with concrete, empowering advice that takes account of modern job market challenges and opportunities. It cuts through widespread misconceptions about STEM careers and funding, offers tips for navigating difficult degree programs, and supplies current or prospective PhDs with the tools to radically transform their post-degree career prospects. How to Make Your PhD Work readers will also find: Detailed discussion of topics including postdoctoral fellowships, nonacademic careers, success in industry, and more Twelve stories from PhD students who talk about their relationship with their advisor, their success with their project, and their transition into their careers Worksheets and case studies designed to help PhDs map out potential career paths An author with extensive experience of the nonacademic job market and a real understanding of the challenges STEM PhDs face How to Make Your PhD Work is ideal for any STEM PhD student, prospective student, or early career researcher looking to improve their positions in the job market. |
| flatiron data science bootcamp: Learning Python Mark Lutz, 2013-06-12 Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code. Explore Python’s major built-in object types such as numbers, lists, and dictionaries Create and process objects with Python statements, and learn Python’s general syntax model Use functions to avoid code redundancy and package code for reuse Organize statements, functions, and other tools into larger components with modules Dive into classes: Python’s object-oriented programming tool for structuring code Write large programs with Python’s exception-handling model and development tools Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing |
| flatiron data science bootcamp: Head First Python Paul Barry, 2016-11-21 Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works. |
| flatiron data science bootcamp: Theory of Games and Statistical Decisions David A. Blackwell, M. A. Girshick, 2012-06-14 Evaluating statistical procedures through decision and game theory, as first proposed by Neyman and Pearson and extended by Wald, is the goal of this problem-oriented text in mathematical statistics. First-year graduate students in statistics and other students with a background in statistical theory and advanced calculus will find a rigorous, thorough presentation of statistical decision theory treated as a special case of game theory. The work of Borel, von Neumann, and Morgenstern in game theory, of prime importance to decision theory, is covered in its relevant aspects: reduction of games to normal forms, the minimax theorem, and the utility theorem. With this introduction, Blackwell and Professor Girshick look at: Values and Optimal Strategies in Games; General Structure of Statistical Games; Utility and Principles of Choice; Classes of Optimal Strategies; Fixed Sample-Size Games with Finite Ω and with Finite A; Sufficient Statistics and the Invariance Principle; Sequential Games; Bayes and Minimax Sequential Procedures; Estimation; and Comparison of Experiments. A few topics not directly applicable to statistics, such as perfect information theory, are also discussed. Prerequisites for full understanding of the procedures in this book include knowledge of elementary analysis, and some familiarity with matrices, determinants, and linear dependence. For purposes of formal development, only discrete distributions are used, though continuous distributions are employed as illustrations. The number and variety of problems presented will be welcomed by all students, computer experts, and others using statistics and game theory. This comprehensive and sophisticated introduction remains one of the strongest and most useful approaches to a field which today touches areas as diverse as gambling and particle physics. |
| flatiron data science bootcamp: Program Or be Programmed Douglas Rushkoff, 2010 Is the internet good or bad? How can technology be directed? In this spirited, accessible poetics of new media, Rushkoff picks up where Marshall McLuhan left off, helping readers come to recognise programming as the new literacy of the digital age and as a template through which to see beyond social conventions and power structures that have vexed us for centuries. This is a friendly little book with a big and actionable message. |
| flatiron data science bootcamp: The No Asshole Rule Robert I. Sutton, 2007-02-22 The definitive guide to working with -- and surviving -- bullies, creeps, jerks, tyrants, tormentors, despots, backstabbers, egomaniacs, and all the other assholes who do their best to destroy you at work. What an asshole! How many times have you said that about someone at work? You're not alone! In this groundbreaking book, Stanford University professor Robert I. Sutton builds on his acclaimed Harvard Business Review article to show you the best ways to deal with assholes...and why they can be so destructive to your company. Practical, compassionate, and in places downright funny, this guide offers: Strategies on how to pinpoint and eliminate negative influences for good Illuminating case histories from major organizations A self-diagnostic test and a program to identify and keep your own inner jerk from coming out The No Asshole Rule is a New York Times, Wall Street Journal, USA Today and Business Week bestseller. |
| flatiron data science bootcamp: Practical Object-Oriented Design Sandi Metz, 2018-07-10 The Complete Guide to Writing Maintainable, Manageable, Pleasing, and Powerful Object-Oriented Applications Object-oriented programming languages exist to help you create beautiful, straightforward applications that are easy to change and simple to extend. Unfortunately, the world is awash with object-oriented (OO) applications that are difficult to understand and expensive to change. Practical Object-Oriented Design, Second Edition, immerses you in an OO mindset and teaches you powerful, real-world, object-oriented design techniques with simple and practical examples. Sandi Metz demonstrates how to build new applications that can “survive success” and repair existing applications that have become impossible to change. Each technique is illustrated with extended examples in the easy-to-understand Ruby programming language, all downloadable from the companion website, poodr.com. Fully updated for Ruby 2.5, this guide shows how to Decide what belongs in a single class Avoid entangling objects that should be kept separate Define flexible interfaces among objects Reduce programming overhead costs with duck typing Successfully apply inheritance Build objects via composition Whatever your previous object-oriented experience, this concise guide will help you achieve the superior outcomes you’re looking for. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| flatiron data science bootcamp: Ace the Data Science Interview Kevin Huo, Nick Singh, 2021 |
| flatiron data science bootcamp: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| flatiron data science bootcamp: Refactoring to Patterns Joshua Kerievsky, 2005 Kerievsky lays the foundation for maximizing the use of design patterns by helping the reader view them in the context of refactorings. He ties together two of the most popular methods in software engineering today--refactoring and design patterns--as he helps the experienced developer create more robust software. |
| flatiron data science bootcamp: Java Programming Ralph Bravaco, Shai Simonson, 2009-02-01 Java Programming, From The Ground Up, with its flexible organization, teaches Java in a way that is refreshing, fun, interesting and still has all the appropriate programming pieces for students to learn. The motivation behind this writing is to bring a logical, readable, entertaining approach to keep your students involved. Each chapter has a Bigger Picture section at the end of the chapter to provide a variety of interesting related topics in computer science. The writing style is conversational and not overly technical so it addresses programming concepts appropriately. Because of the flexibile organization of the text, it can be used for a one or two semester introductory Java programming class, as well as using Java as a second language. The text contains a large variety of carefully designed exercises that are more effective than the competition. |
| flatiron data science bootcamp: Robot-Proof, revised and updated edition Joseph E. Aoun, 2024-10-15 A fresh look at a “robot-proof” education in the new age of generative AI. In 2017, Robot-Proof, the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a result, we must now learn not only to be conversant with these technologies, but also to comprehend and deploy their outputs. In this revised and updated edition, Joseph Aoun rethinks the university’s mission for a world transformed by AI, advocating for the lifelong endeavor of a “robot-proof” education. Aoun puts forth a framework for a new curriculum, humanics, which integrates technological, data, and human literacies in an experiential setting, and he renews the call for universities to embrace lifelong learning through a social compact with government, employers, and learners themselves. Drawing on the latest developments and debates around generative AI, Robot-Proof is a blueprint for the university as a force for human reinvention in an era of technological change—an era in which we must constantly renegotiate the shifting boundaries between artificial intelligence and the capacities that remain uniquely human. |
| flatiron data science bootcamp: Nice Is Just a Place in France Betches, 2013-03-12 LOOK, MAYBE YOU’RE A NICE GIRL, but we’re guessing you’re more like us or you probably wouldn’t have picked up this book. Not that we have a problem with girls who are nice people. But being nice is just not the way to get what you want. And this book is about getting what you want. Not in like a finding happiness, giving back to the world, being grateful for what you have sort of way. But in a ruling your world, being the most desired, powerful badass in the room way, so you can come out on top of any situation: guys, career, friends, enemies, whatever. How does a betch make that happen? Here are some highlights: DON’T BE EASY. DON’T BE POOR. DON’T BE UGLY. We didn’t come up with these life lessons. We’re just the ones who wrote it all down. This is not self-help. Self-help is for fat people and divorcées. This is how to deal with your problems when you have no problems. You’re welcome. |
| flatiron data science bootcamp: Learn to Program Chris Pine, 2021-06-17 It's easier to learn how to program a computer than it has ever been before. Now everyone can learn to write programs for themselves - no previous experience is necessary. Chris Pine takes a thorough, but lighthearted approach that teaches you the fundamentals of computer programming, with a minimum of fuss or bother. Whether you are interested in a new hobby or a new career, this book is your doorway into the world of programming. Computers are everywhere, and being able to program them is more important than it has ever been. But since most books on programming are written for other programmers, it can be hard to break in. At least it used to be. Chris Pine will teach you how to program. You'll learn to use your computer better, to get it to do what you want it to do. Starting with small, simple one-line programs to calculate your age in seconds, you'll see how to write interactive programs, to use APIs to fetch live data from the internet, to rename your photos from your digital camera, and more. You'll learn the same technology used to drive modern dynamic websites and large, professional applications. Whether you are looking for a fun new hobby or are interested in entering the tech world as a professional, this book gives you a solid foundation in programming. Chris teaches the basics, but also shows you how to think like a programmer. You'll learn through tons of examples, and through programming challenges throughout the book. When you finish, you'll know how and where to learn more - you'll be on your way. What You Need: All you need to learn how to program is a computer (Windows, macOS, or Linux) and an internet connection. Chris Pine will lead you through setting set up with the software you will need to start writing programs of your own. |
| flatiron data science bootcamp: Apprenticeship Patterns Dave Hoover, Adewale Oshineye, 2009-10-02 Are you doing all you can to further your career as a software developer? With today's rapidly changing and ever-expanding technologies, being successful requires more than technical expertise. To grow professionally, you also need soft skills and effective learning techniques. Honing those skills is what this book is all about. Authors Dave Hoover and Adewale Oshineye have cataloged dozens of behavior patterns to help you perfect essential aspects of your craft. Compiled from years of research, many interviews, and feedback from O'Reilly's online forum, these patterns address difficult situations that programmers, administrators, and DBAs face every day. And it's not just about financial success. Apprenticeship Patterns also approaches software development as a means to personal fulfillment. Discover how this book can help you make the best of both your life and your career. Solutions to some common obstacles that this book explores in-depth include: Burned out at work? Nurture Your Passion by finding a pet project to rediscover the joy of problem solving. Feeling overwhelmed by new information? Re-explore familiar territory by building something you've built before, then use Retreat into Competence to move forward again. Stuck in your learning? Seek a team of experienced and talented developers with whom you can Be the Worst for a while. Brilliant stuff! Reading this book was like being in a time machine that pulled me back to those key learning moments in my career as a professional software developer and, instead of having to learn best practices the hard way, I had a guru sitting on my shoulder guiding me every step towards master craftsmanship. I'll certainly be recommending this book to clients. I wish I had this book 14 years ago!-Russ Miles, CEO, OpenCredo |
| flatiron data science bootcamp: Learning to Program Steven Foote, 2014 Learning to Program will help students build a solid foundation in programming that can prepare them to achieve just about any programming goal. Whether they want to become a professional software programmer, learn how to more effectively communicate with programmers, or are just curious about how programming works, this book is a great first step in helping to get there. |
| flatiron data science bootcamp: Design Patterns in Ruby (Adobe Reader) Russ Olsen, 2007-12-10 Praise for Design Patterns in Ruby Design Patterns in Ruby documents smart ways to resolve many problems that Ruby developers commonly encounter. Russ Olsen has done a great job of selecting classic patterns and augmenting these with newer patterns that have special relevance for Ruby. He clearly explains each idea, making a wealth of experience available to Ruby developers for their own daily work. —Steve Metsker, Managing Consultant with Dominion Digital, Inc. This book provides a great demonstration of the key 'Gang of Four' design patterns without resorting to overly technical explanations. Written in a precise, yet almost informal style, this book covers enough ground that even those without prior exposure to design patterns will soon feel confident applying them using Ruby. Olsen has done a great job to make a book about a classically 'dry' subject into such an engaging and even occasionally humorous read. —Peter Cooper This book renewed my interest in understanding patterns after a decade of good intentions. Russ picked the most useful patterns for Ruby and introduced them in a straightforward and logical manner, going beyond the GoF's patterns. This book has improved my use of Ruby, and encouraged me to blow off the dust covering the GoF book. —Mike Stok Design Patterns in Ruby is a great way for programmers from statically typed objectoriented languages to learn how design patterns appear in a more dynamic, flexible language like Ruby. —Rob Sanheim, Ruby Ninja, Relevance Most design pattern books are based on C++ and Java. But Ruby is different—and the language's unique qualities make design patterns easier to implement and use. In this book, Russ Olsen demonstrates how to combine Ruby's power and elegance with patterns, and write more sophisticated, effective software with far fewer lines of code. After reviewing the history, concepts, and goals of design patterns, Olsen offers a quick tour of the Ruby language—enough to allow any experienced software developer to immediately utilize patterns with Ruby. The book especially calls attention to Ruby features that simplify the use of patterns, including dynamic typing, code closures, and mixins for easier code reuse. Fourteen of the classic Gang of Four patterns are considered from the Ruby point of view, explaining what problems each pattern solves, discussing whether traditional implementations make sense in the Ruby environment, and introducing Ruby-specific improvements. You'll discover opportunities to implement patterns in just one or two lines of code, instead of the endlessly repeated boilerplate that conventional languages often require. Design Patterns in Ruby also identifies innovative new patterns that have emerged from the Ruby community. These include ways to create custom objects with metaprogramming, as well as the ambitious Rails-based Convention Over Configuration pattern, designed to help integrate entire applications and frameworks. Engaging, practical, and accessible, Design Patterns in Ruby will help you build better software while making your Ruby programming experience more rewarding. |
| flatiron data science bootcamp: Computational Finance and Financial Econometrics Eric Zivot, 2017-01-15 This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. The author explains how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios. |
| flatiron data science bootcamp: Lower Ed Tressie McMillan Cottom, 2017-02-28 More than two million students are enrolled in for-profit colleges, from the small family-run operations to the behemoths brandished on billboards, subway ads, and late-night commercials. These schools have been around just as long as their bucolic not-for-profit counterparts, yet shockingly little is known about why they have expanded so rapidly in recent years—during the so-called Wall Street era of for-profit colleges. In Lower Ed Tressie McMillan Cottom—a bold and rising public scholar, herself once a recruiter at two for-profit colleges—expertly parses the fraught dynamics of this big-money industry to show precisely how it is part and parcel of the growing inequality plaguing the country today. McMillan Cottom discloses the shrewd recruitment and marketing strategies that these schools deploy and explains how, despite the well-documented predatory practices of some and the campus closings of others, ending for-profit colleges won't end the vulnerabilities that made them the fastest growing sector of higher education at the turn of the twenty-first century. And she doesn't stop there. With sharp insight and deliberate acumen, McMillan Cottom delivers a comprehensive view of postsecondary for-profit education by illuminating the experiences of the everyday people behind the shareholder earnings, congressional battles, and student debt disasters. The relatable human stories in Lower Ed—from mothers struggling to pay for beauty school to working class guys seeking good jobs to accomplished professionals pursuing doctoral degrees—illustrate that the growth of for-profit colleges is inextricably linked to larger questions of race, gender, work, and the promise of opportunity in America. Drawing on more than one hundred interviews with students, employees, executives, and activists, Lower Ed tells the story of the benefits, pitfalls, and real costs of a for-profit education. It is a story about broken social contracts; about education transforming from a public interest to a private gain; and about all Americans and the challenges we face in our divided, unequal society. |
| flatiron data science bootcamp: 101 Asian Dishes You Need to Cook Before You Die Jet Tila, 2017-06-27 Celebrity chef, Asian cooking expert and TV personality Jet Tila has compiled the best-of-the-best 101 Eastern recipes that every home cook needs to try before they die! The dishes are authentic yet unique to Jet--drawn from his varied cooking experience, unique heritage and travels. The dishes are also approachable--with simplified techniques, weeknight-friendly total cook times and ingredients commonly found in most urban grocery stores today. |
| flatiron data science bootcamp: The Future of University Credentials Sean R. Gallagher, 2022-07-14 2017 Phillip E. Frandson Award for Literature in the Field of Professional, Continuing, and/or Online Education, University Professional and Continuing Education Association (UPCEA) The Future of University Credentials offers a thorough and urgently needed overview of the burgeoning world of university degrees and credentials. At a time of heightened attention to how universities and colleges are preparing young people for the working world, questions about the meaning and value of university credentials have become especially prominent. Sean Gallagher guides us through this fast-changing terrain, providing much-needed context, details, and insights. The book casts a wide net, focusing on traditional higher education degrees and on the myriad certificates and other postsecondary awards that universities and other institutions now issue. He describes the entire ecosystem of credentials, including universities and colleges, employers, government agencies, policy makers and influencers—and, not least, the students whose futures are profoundly affected by these certifications. And he looks intently at where university credentials might be headed, as educational institutions seek to best serve students and employers in a rapidly changing world. The result is an unprecedented, comprehensive look at the current credentialing landscape in higher education—as well as at the future challenges and opportunities for this vital field. |
| flatiron data science bootcamp: Smokin' with Myron Mixon Myron Mixon, Kelly Alexander, 2011-05-10 The winningest man in barbecause shares the secrets of his success. Rule number one? Keep it simple. In the world of competitive barbecue, nobody’s won more prize money, more trophies, or more adulation than Myron Mixon. And he comes by it honestly: From the time he was old enough to stoke a pit, Mixon learned the art of barbecue at his father’s side. He grew up to expand his parent’s sauce business, Jack’s Old South, and in the process became the leader of the winningest team in competitive barbecue. It’s Mixon’s combination of killer instinct and killer recipes that has led him to three world championships and more than 180 grand championships and made him the breakout star of TLC’s BBQ Pitmasters. Now, for the first time, Mixon’s stepping out from behind his rig to teach you how he does it. Rule number one: People always try to overthink barbecue and make it complicated. Don’t do it! Mixon will show you how you can apply his “keep it simple” mantra in your own backyard. He’ll take you to the front lines of barbecue and teach you how to turn out ’cue like a seasoned pro. You’ll learn to cook like Mixon does when he’s on the road competing and when he’s at home, with great tips on • the basics, from choosing the right wood to getting the best smoker or grill • the formulas for the marinades, rubs, injections, and sauces you’ll need • the perfect ways to cook up hog, ribs, brisket, and chicken, including Mixon’s famous Cupcake Chicken Mixon shares more than 75 of his award-winning recipes—including one for the most sinful burger you’ll ever eat—and advice that will end any anxiety over cooking times and temps and change your backyard barbecues forever. He also fills you in on how he rose to the top of the competitive barbecue universe and his secrets for succulent success. Complete with mouth-watering photos, Smokin’ with Myron Mixon will fire you up for a tasty time. |
| flatiron data science bootcamp: Essential C++ Stanley B. Lippman, 2000 Finally, a great introduction to ANCI C++ for working programmers! Lippmann--who worked under the leadership of Bjarne Stroustrup, wrote the classic C++ Primer, and now works as a C++ programmer at DreamWorks--teaches programmers exactly what they need to know to get immediate results. From start to finish, each concept and technique is presented through real programs designed to solve the problems C++ programmers are most likely to encounter. |
| flatiron data science bootcamp: The Pragmatic Programmer Andrew Hunt, David Thomas, 1999-10-20 What others in the trenches say about The Pragmatic Programmer... “The cool thing about this book is that it’s great for keeping the programming process fresh. The book helps you to continue to grow and clearly comes from people who have been there.” — Kent Beck, author of Extreme Programming Explained: Embrace Change “I found this book to be a great mix of solid advice and wonderful analogies!” — Martin Fowler, author of Refactoring and UML Distilled “I would buy a copy, read it twice, then tell all my colleagues to run out and grab a copy. This is a book I would never loan because I would worry about it being lost.” — Kevin Ruland, Management Science, MSG-Logistics “The wisdom and practical experience of the authors is obvious. The topics presented are relevant and useful.... By far its greatest strength for me has been the outstanding analogies—tracer bullets, broken windows, and the fabulous helicopter-based explanation of the need for orthogonality, especially in a crisis situation. I have little doubt that this book will eventually become an excellent source of useful information for journeymen programmers and expert mentors alike.” — John Lakos, author of Large-Scale C++ Software Design “This is the sort of book I will buy a dozen copies of when it comes out so I can give it to my clients.” — Eric Vought, Software Engineer “Most modern books on software development fail to cover the basics of what makes a great software developer, instead spending their time on syntax or technology where in reality the greatest leverage possible for any software team is in having talented developers who really know their craft well. An excellent book.” — Pete McBreen, Independent Consultant “Since reading this book, I have implemented many of the practical suggestions and tips it contains. Across the board, they have saved my company time and money while helping me get my job done quicker! This should be a desktop reference for everyone who works with code for a living.” — Jared Richardson, Senior Software Developer, iRenaissance, Inc. “I would like to see this issued to every new employee at my company....” — Chris Cleeland, Senior Software Engineer, Object Computing, Inc. “If I’m putting together a project, it’s the authors of this book that I want. . . . And failing that I’d settle for people who’ve read their book.” — Ward Cunningham Straight from the programming trenches, The Pragmatic Programmer cuts through the increasing specialization and technicalities of modern software development to examine the core process--taking a requirement and producing working, maintainable code that delights its users. It covers topics ranging from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse. Read this book, and you'll learn how to Fight software rot; Avoid the trap of duplicating knowledge; Write flexible, dynamic, and adaptable code; Avoid programming by coincidence; Bullet-proof your code with contracts, assertions, and exceptions; Capture real requirements; Test ruthlessly and effectively; Delight your users; Build teams of pragmatic programmers; and Make your developments more precise with automation. Written as a series of self-contained sections and filled with entertaining anecdotes, thoughtful examples, and interesting analogies, The Pragmatic Programmer illustrates the best practices and major pitfalls of many different aspects of software development. Whether you're a new coder, an experienced programmer, or a manager responsible for software projects, use these lessons daily, and you'll quickly see improvements in personal productivity, accuracy, and job satisfaction. You'll learn skills and develop habits and attitudes that form the foundation for long-term success in your career. You'll become a Pragmatic Programmer. |
| flatiron data science bootcamp: Data Science from Scratch Joel Grus, 2015-04-14 Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases |
| flatiron data science bootcamp: Learning Node Shelley Powers, 2012-08-27 Take your web development skills from browser to server with Node—and learn how to write fast, highly scalable network applications on this JavaScript-based platform. With this hands-on guide, you’ll quickly master Node’s core fundamentals, gain experience with several built-in and contributed modules, and learn the differences and parallels between client- and server-side programming. Get up to speed on Node’s event-driven, asynchronous I/O model for developing data-intensive applications that are frequently accessed but computationally simple. If you’re comfortable working with JavaScript, this book provides numerous programming and deployment examples to help you take advantage of server-side development with Node. Explore Node’s unique approach to asynchronous development Build sample Node applications with the Express framework and Connect middleware Use NoSQL solutions such as Redis and MongoDB—and explore Node’s relational database modules Work with PDF files, serve HTML5 media, and create graphics with Canvas Set up bidirectional communication between browser and server with WebSockets Learn in-depth practices for debugging and testing your applications Deploy Node applications in the cloud or on your own system Learning Node will make it easy for someone from any programming background to get a grip on Node.js and build amazing projects. —Tom Hughes-Croucher, co-author of Node: Up and Running (O’Reilly) |
| flatiron data science bootcamp: Most Likely to Succeed Tony Wagner, Ted Dintersmith, 2015-08-18 An urgent call for the radical re-imagining of American education so that we better equip students for the realities of the twenty-first century. |
| flatiron data science bootcamp: Deep Learning Illustrated Jon Krohn, Grant Beyleveld, Aglaé Bassens, 2019-08-05 The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come. – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| flatiron data science bootcamp: Get Rich Click! Marc Ostrofsky, 2013-01-08 The Internet is changing the way business is conducted and fortunes are made. Get Rich Click! shows readers how to jump in and begin making money online immediately. |
| flatiron data science bootcamp: Production-Ready Microservices Susan J. Fowler, 2016-11-30 One of the biggest challenges for organizations that have adopted microservice architecture is the lack of architectural, operational, and organizational standardization. After splitting a monolithic application or building a microservice ecosystem from scratch, many engineers are left wondering what’s next. In this practical book, author Susan Fowler presents a set of microservice standards in depth, drawing from her experience standardizing over a thousand microservices at Uber. You’ll learn how to design microservices that are stable, reliable, scalable, fault tolerant, performant, monitored, documented, and prepared for any catastrophe. Explore production-readiness standards, including: Stability and Reliability: develop, deploy, introduce, and deprecate microservices; protect against dependency failures Scalability and Performance: learn essential components for achieving greater microservice efficiency Fault Tolerance and Catastrophe Preparedness: ensure availability by actively pushing microservices to fail in real time Monitoring: learn how to monitor, log, and display key metrics; establish alerting and on-call procedures Documentation and Understanding: mitigate tradeoffs that come with microservice adoption, including organizational sprawl and technical debt |
| flatiron data science bootcamp: Cisco CCNA Routing and Switching 200-120 Official Cert Guide Library Wendell Odom, 2013 Cisco Press is the official publisher for the New CCENT & CCNA Routing and Switching Certifications. The New Edition of the Best-Selling two-book value priced CCNA Official Cert Guide Library includes Updated Content, New Exercises, 8 Practice Exams, and 150 Minutes of Video Training -- PLUS the CCENT and CCNA Network Simulator Lite Editions with 26 Free Network Simulator Labs. CCNA 200-120 Official Cert Guide Library is a comprehensive review and package for the latest CCNA exams. The two books contained in this package, CCENT / CCNA ICND1 100-101 Official Cert Guide and CCNA ICND2 200-101 Official Cert Guide, present complete reviews and a more challenging and realistic preparation experience. The books have been fully updated to refresh the content for the latest CCNA exam topics and enhance certain key topics that are critical for exam success. Best-selling author and expert instructor Wendell Odom shares preparation hints and test-taking tips, helping you identify areas of weakness and improve both your conceptual knowledge and hands-on skills. These official study guides help you master all the topics on the CCNA exams, including: Networking fundamentals Ethernet LANs and switches IPv4 addressing and subnetting Operating Cisco routers Configuring OSPF ACLs and NAT IPv6 fundamentals, implementation, and troubleshooting LAN switching IPv4 routing VPNs OSPF and EIGRP configuration and troubleshooting Wide area networks and Frame Relay Network management Well regarded for its level of detail, study plans, assessment features, challenging review questions and exercises, video instruction, and hands-on labs, these official study guides help you master the concepts and techniques that ensure your exam success. CCNA 200-120 Official Cert Guide Library is part of a recommended learning path from Cisco that includes simulation and hands-on training from authorized Cisco Learning Partners and self-study products from Cisco Press. 1587143879 / 9781587143878 CCNA Routing and Switching 200-120 Official Cert Guide Library 1/e Package consists of: 0131357549 / 9780131357549 TWO INCH MYLAR CLEAR WAFER SEAL 0133372006 / 9780133372007 Empty Slipcase for Exam 29 Cert Library 1587143739 / 9781587143731 CCNA Routing and Switching ICND2 200-101 Official Cert Guide 1587143852 / 9781587143854 CCENT/CCNA ICND1 100-101 Official Cert Guide |
| flatiron data science bootcamp: Alternative and independent Caren Arbeit, Alexander Bentz, Emily Forrest Cataldi, Herschel Sanders., 2019-02-19 In recent years, nontraditional workforce training programs have proliferated inside and outside of traditional postsecondary institutions. A subset of these programs, bootcamps, advertise high job placement rates and have been hailed by policymakers as key to training skilled workers. However, few formal data exist on the number, types, prices, location, or other descriptive details of program offerings. We fill this void by studying the universe of bootcamp programs offered as of June 30, 2017. In this report, we discuss the attributes of the 1,010 technology-related programs offered in the United States, Canada, and online. We find more diversity among bootcamp providers and programs than would be expected from public discourse. This primarily relates to the mode of delivery (online vs. in person), intensity (part time/full time), cost, and program types. Based on the data we collected, we present a classification structure for bootcamps focused on five distinct program types. |
| flatiron data science bootcamp: Coders Clive Thompson, 2019 [An] anthropological reckoning with the most powerful tribe in the world today, computer programmers--where they come from, how they think, what makes for greatness in their world, and what should give us pause-- |
| flatiron data science bootcamp: 48 Days to the Work You Love Dan Miller, 2010 Practical instructions from leading vocational thinker Miller reveal how to approach work as more than just a paycheck, but as part of the calling God has placed on each life. |
| flatiron data science bootcamp: Mastering matplotlib Duncan M. McGreggor, 2015-06-29 matplotlib is a Python plotting library that provides a large feature set for a multitude of platforms. Given the depth of the library's legacy and the variety of related open source projects, gaining expert knowledge can be a time-consuming and often confusing process. You'll begin your exciting journey learning about the skills that are necessary in leading technical teams for a visualization project or to become a matplotlib contributor. Supported by highly-detailed IPython Notebooks, this book takes you through the conceptual components underlying the library and then provides a detailed overview of its APIs. From there, you will learn about event handling and how to code for interactive plots. Next you will move on to customization techniques, local configuration of matplotib, and then deployments in Cloud environments. The adventure culminates in an exploration of big data visualization and matplotlib clustering. |
| flatiron data science bootcamp: 2020 Vision: a History of the Future Michael Moe, 2015-10-23 GSV’s aspirational vision for how to address society’s greatest challenge…ensuring that everyone has equal opportunity to participate in the future. |
Flatiron Health | Reimagining the infrastructure of cancer care
Clinicians, researchers, and regulators rely on Flatiron technology and evidence to learn faster and power smarter care for every patient. Because transforming cancer care takes all of us.
Careers | Flatiron Health
A career at Flatiron is a chance to work alongside some of the brightest and most compassionate minds in oncology, technology, and research.
Company | Flatiron Health
FLATIRON HEALTH® is a healthtech company dedicated to improving cancer treatment and advancing research. As the pioneer in real-world evidence for oncology, we provide …
Login - Flatiron
By downloading, using or accessing this App, you agree to be bound by these Terms.If you do not accept these Terms in their entirety, you must not download, use or access this App. Terms in …
Evidence Solutions | Real-World Evidence | Flatiron Health
Flatiron Horizon is the driving force behind our real-world evidence solutions, seamlessly integrating the richest labeled oncology data in the world, Flatiron’s proprietary curation …
Flatiron Health Expands Beyond Real-World Data, Providing End …
Flatiron Health is a healthtech company expanding the possibilities for point of care solutions in oncology and using data for good to power smarter care for every person with cancer. …
Point of Care Solutions for Oncology | Flatiron Health
Designed by oncologists and world-class engineers, Flatiron technology helps cancer centers remain financially viable, run more efficient clinical trials, and stay one step ahead of …
Teams at Flatiron | Flatiron Health
At Flatiron, across our global organization, you’ll find multidisciplinary teams designed to drive global transformation in cancer care, research, and treatment. From software engineers to …
Open Positions | Flatiron Health
Stay in the know by joining our talent community. We’ll keep you up-to-date on all the latest events, activities and opportunities at Flatiron Health.
Expanding the possibilities of oncology care with OncoEMR®
Technology should support the evolution of oncology care, not get in the way. Here’s how Flatiron Health is delivering on the promises of technology by facilitating information flow, reducing …
Flatiron Health | Reimagining the infrastructure of cancer care
Clinicians, researchers, and regulators rely on Flatiron technology and evidence to learn faster and power smarter care for every patient. Because transforming cancer care takes all of us.
Careers | Flatiron Health
A career at Flatiron is a chance to work alongside some of the brightest and most compassionate minds in oncology, technology, and research.
Company | Flatiron Health
FLATIRON HEALTH® is a healthtech company dedicated to improving cancer treatment and advancing research. As the pioneer in real-world evidence for oncology, we provide …
Login - Flatiron
By downloading, using or accessing this App, you agree to be bound by these Terms.If you do not accept these Terms in their entirety, you must not download, use or access this App. Terms in …
Evidence Solutions | Real-World Evidence | Flatiron Health
Flatiron Horizon is the driving force behind our real-world evidence solutions, seamlessly integrating the richest labeled oncology data in the world, Flatiron’s proprietary curation …
Flatiron Health Expands Beyond Real-World Data, Providing End …
Flatiron Health is a healthtech company expanding the possibilities for point of care solutions in oncology and using data for good to power smarter care for every person with cancer. …
Point of Care Solutions for Oncology | Flatiron Health
Designed by oncologists and world-class engineers, Flatiron technology helps cancer centers remain financially viable, run more efficient clinical trials, and stay one step ahead of …
Teams at Flatiron | Flatiron Health
At Flatiron, across our global organization, you’ll find multidisciplinary teams designed to drive global transformation in cancer care, research, and treatment. From software engineers to …
Open Positions | Flatiron Health
Stay in the know by joining our talent community. We’ll keep you up-to-date on all the latest events, activities and opportunities at Flatiron Health.
Expanding the possibilities of oncology care with OncoEMR®
Technology should support the evolution of oncology care, not get in the way. Here’s how Flatiron Health is delivering on the promises of technology by facilitating information flow, reducing …
