Galvanize Data Science Immersive

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  galvanize data science immersive: Getting Started with Streamlit for Data Science Tyler Richards, 2021-08-20 Create, deploy, and test your Python applications, analyses, and models with ease using Streamlit Key Features Learn how to showcase machine learning models in a Streamlit application effectively and efficiently Become an expert Streamlit creator by getting hands-on with complex application creation Discover how Streamlit enables you to create and deploy apps effortlessly Book DescriptionStreamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.What you will learn Set up your first development environment and create a basic Streamlit app from scratch Explore methods for uploading, downloading, and manipulating data in Streamlit apps Create dynamic visualizations in Streamlit using built-in and imported Python libraries Discover strategies for creating and deploying machine learning models in Streamlit Use Streamlit sharing for one-click deployment Beautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebar Implement best practices for prototyping your data science work with Streamlit Who this book is for This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you’re a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.
  galvanize data science immersive: Beginning iPhone Development with Swift 3 Molly Maskrey, Kim Topley, David Mark, Fredrik Olsson, JEFF LAMARCHE, 2016-11-17 Create your very own apps for the latest iOS devices. You'll start with the basics, and then work your way through the process of downloading and installing Xcode and the iOS 10 SDK, and then guides you though the creation of your first simple application. Assuming little or no working knowledge of the Swift programming language, and written in a friendly, easy-to-follow style, Beginning iPhone Development with Swift 3 offers a comprehensive course in iPhone and iPad programming. In this third edition of the best-selling book, you’ll learn how to integrate all the interface elements iOS users have come to know and love, such as buttons, switches, pickers, toolbars, and sliders. Every single sample app in the book has been rebuilt from scratch using the latest Xcode and the latest iOS 10-specific project templates, and designed to take advantage of the latest Xcode features. Discover brand-new technologies, as well as significant updates to existing tools. You’ll master a variety of design patterns, from the simplest single view to complex hierarchical drill-downs. The art of table building will be demystified, and you’ll learn how to save your data using the iOS file system. You’ll also learn how to save and retrieve your data using a variety of persistence techniques, including Core Data and SQLite. And there’s much more! What You Will Learn Develop your own bestselling iPhone and iPad apps Utilize Swift playgrounds Display data in Table Views Draw to the screen using Core Graphics Use iOS sensor capabilities to map your world Get your app to work with iCloud and more Who This Book is For Anyone who wants to start developing for iPhone and iPad.
  galvanize data science immersive: A New U Ryan Craig, 2018-09-11 Every year, the cost of a four-year degree goes up, and the value goes down. But for many students, there's a better answer. So many things are getting faster and cheaper. Movies stream into your living room, without ticket or concession-stand costs. The world's libraries are at your fingertips instantly, and for free. So why is a college education the only thing that seems immune to change? Colleges and universities operate much as they did 40 years ago, with one major exception: tuition expenses have risen dramatically. What's more, earning a degree takes longer than ever before, with the average time to graduate now over five years. As a result, graduates often struggle with enormous debt burdens. Even worse, they often find that degrees did not prepare them to obtain and succeed at good jobs in growing sectors of the economy. While many learners today would thrive with an efficient and affordable postsecondary education, the slow and pricey road to a bachelor's degree is starkly the opposite. In A New U: Faster + Cheaper Alternatives to College, Ryan Craig documents the early days of a revolution that will transform—or make obsolete—many colleges and universities. Alternative routes to great first jobs that do not involve a bachelor's degree are sprouting up all over the place. Bootcamps, income-share programs, apprenticeships, and staffing models are attractive alternatives to great jobs in numerous growing sectors of the economy: coding, healthcare, sales, digital marketing, finance and accounting, insurance, and data analytics. A New U is the first roadmap to these groundbreaking programs, which will lead to more student choice, better matches with employers, higher return on investment of cost and time, and stronger economic growth.
  galvanize data science immersive: Sourcing and Recruitment Handbook Jay Tarimala, 2020-11-10 The sourcing and recruitment community has come a long way from what it used to be 20 years back and as recently as 5 years back and the amount of technology changes has kept everyone on the tenterhooks. The methods that you would adopt or Boolean strings that used to work today may not work tomorrow and there is a constant learning curve to keep oneself updated and also brings a healthy level of competition among individuals eager to show their wares. The volume based or niche skills hiring has become a race to the finish. The individuals with the super sourcing as well as relationship management skills tend to be more often than not the winners in the end. The recruitment community looks to find the needle in the haystack every day to find the right candidate to fulfill the hiring manager mandate. The ever bulging stock of search strings, productivity tricks and their ways of thinking they implement are a stuff of legend. The tools do not make a Sourcer or recruiter but they should always be seen as an assistant to free up their time for more productive conversations with prospective candidates. This exercise is an attempt to equip the Talent Acquisition community with the various ways and methods to optimize their time and find the relevant information (trends, movers and shakers etc.) to be better prepared to find relevant candidates for their clients (internal or external). It is by no means an exhaustive list but a start nonetheless.
  galvanize data science immersive: Data Mining and Predictive Analytics Daniel T. Larose, 2015-02-19 Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
  galvanize data science immersive: 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.
  galvanize data science immersive: Practical Data Science with Python Nathan George, 2021-09-30 Learn to effectively manage data and execute data science projects from start to finish using Python Key FeaturesUnderstand and utilize data science tools in Python, such as specialized machine learning algorithms and statistical modelingBuild a strong data science foundation with the best data science tools available in PythonAdd value to yourself, your organization, and society by extracting actionable insights from raw dataBook Description Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science. The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion. As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments. By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source. What you will learnUse Python data science packages effectivelyClean and prepare data for data science work, including feature engineering and feature selectionData modeling, including classic statistical models (such as t-tests), and essential machine learning algorithms, such as random forests and boosted modelsEvaluate model performanceCompare and understand different machine learning methodsInteract with Excel spreadsheets through PythonCreate automated data science reports through PythonGet to grips with text analytics techniquesWho this book is for The book is intended for beginners, including students starting or about to start a data science, analytics, or related program (e.g. Bachelor’s, Master’s, bootcamp, online courses), recent college graduates who want to learn new skills to set them apart in the job market, professionals who want to learn hands-on data science techniques in Python, and those who want to shift their career to data science. The book requires basic familiarity with Python. A getting started with Python section has been included to get complete novices up to speed.
  galvanize data science immersive: A Mind for Numbers Barbara A. Oakley, 2014-07-31 Engineering professor Barbara Oakley knows firsthand how it feels to struggle with math. In her book, she offers you the tools needed to get a better grasp of that intimidating but inescapable field.
  galvanize data science immersive: Artificial Intelligence and the Future of Defense Stephan De Spiegeleire, Matthijs Maas, Tim Sweijs, 2017-05-17 Artificial intelligence (AI) is on everybody’s minds these days. Most of the world’s leading companies are making massive investments in it. Governments are scrambling to catch up. Every single one of us who uses Google Search or any of the new digital assistants on our smartphones has witnessed first-hand how quickly these developments now go. Many analysts foresee truly disruptive changes in education, employment, health, knowledge generation, mobility, etc. But what will AI mean for defense and security? In a new study HCSS offers a unique perspective on this question. Most studies to date quickly jump from AI to autonomous (mostly weapon) systems. They anticipate future armed forces that mostly resemble today’s armed forces, engaging in fairly similar types of activities with a still primarily industrial-kinetic capability bundle that would increasingly be AI-augmented. The authors of this study argue that AI may have a far more transformational impact on defense and security whereby new incarnations of ‘armed force’ start doing different things in novel ways. The report sketches a much broader option space within which defense and security organizations (DSOs) may wish to invest in successive generations of AI technologies. It suggests that some of the most promising investment opportunities to start generating the sustainable security effects that our polities, societies and economies expect may lie in in the realms of prevention and resilience. Also in those areas any large-scale application of AI will have to result from a preliminary open-minded (on all sides) public debate on its legal, ethical and privacy implications. The authors submit, however, that such a debate would be more fruitful than the current heated discussions about ‘killer drones’ or robots. Finally, the study suggests that the advent of artificial super-intelligence (i.e. AI that is superior across the board to human intelligence), which many experts now put firmly within the longer-term planning horizons of our DSOs, presents us with unprecedented risks but also opportunities that we have to start to explore. The report contains an overview of the role that ‘intelligence’ - the computational part of the ability to achieve goals in the world - has played in defense and security throughout human history; a primer on AI (what it is, where it comes from and where it stands today - in both civilian and military contexts); a discussion of the broad option space for DSOs it opens up; 12 illustrative use cases across that option space; and a set of recommendations for - especially - small- and medium sized defense and security organizations.
  galvanize data science immersive: Getting Your First Job For Dummies Roberto Angulo, 2017-12-26 Find—and land—your first job! Finding a job can seem daunting, especially when it's a brand new experience. There's a lot to know, and often a lot of pressure. Written by the founder of AfterCollege.com, Getting Your First Job For Dummies is designed to take the stress out of the job search process and help you get an offer. In this book, you'll discover how to identify your talents and strengths, use your network to your advantage, interview with confidence, and evaluate an offer. Written in plain English and packed with step-by-step instructions, it'll have you writing customized resumes, conducting company research, and utilizing online job search sites, faster than you can say 'I got the job!' Determine what kind of job suits your interests and skills Write a compelling cover letter Know what to expect in an interview Effectively negotiate an offer Whether you're still in school or navigating the world as a recent graduate, Getting Your First Job For Dummies arms you with the skills and confidence to make getting your first job an exciting and enjoyable process.
  galvanize data science immersive: Big Data in Education Ben Williamson, 2017-07-24 Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
  galvanize data science immersive: Designing Sustainable Futures Joseph Press, Manuela Celi, 2024-10-28 We are in a decisive decade that demands more inspired and informed practitioners who can use positive futures to rebalance the present. The book you hold seeks to be a thought‐provoking approach to imagine, create, and lead the journey to a more sustainable world – where a spectrum of choices, including regenerative practices, await conscientious citizens, companies, and communities. With this objective, and to help reverse the megatrends of economic disparity, social injustice, and climate change, the Institute for the Future (IFTF) and the Design Department of the Politecnico di Milano came together to prototype an approach to prepare all practitioners who seek to leverage the future to infuse our present with more impact and agency. Guided by global experts and inspired by a growing network of future‐makers, the authors share essential insights from this emerging landscape, offering thought‐provoking theory, innovative experiments, real‐world experiences, and practitioner stories. We draw insight and inspiration from many contemporary theories and practices, including strategic foresight, experiential futures, speculative design, design fiction, systems design, participatory design, and transformative leadership, and an emerging entry with genAI‐augmented design. Regardless of whether you have a design or management background, or want to create a for‐profit or non‐profit, this book enables professionals across industries, as well as students preparing for a career in strategy, innovation, or transformation, the knowledge, skills, and confidence to strengthen resilience and guide the transition to the more sustainable practices of a better world.
  galvanize data science immersive: Phantasmal Media D. Fox Harrell, 2013-11-08 An argument that great expressive power of computational media arises from the construction of phantasms—blends of cultural ideas and sensory imagination. In Phantasmal Media, D. Fox Harrell considers the expressive power of computational media. He argues, forcefully and persuasively, that the great expressive potential of computational media comes from the ability to construct and reveal phantasms—blends of cultural ideas and sensory imagination. These ubiquitous and often-unseen phantasms—cognitive phenomena that include sense of self, metaphors, social categories, narrative, and poetic thinking—influence almost all our everyday experiences. Harrell offers an approach for understanding and designing computational systems that have the power to evoke these phantasms, paying special attention to the exposure of oppressive phantasms and the creation of empowering ones. He argues for the importance of cultural content, diverse worldviews, and social values in computing. The expressive power of phantasms is not purely aesthetic, he contends; phantasmal media can express and construct the types of meaning central to the human condition. Harrell discusses, among other topics, the phantasm as an orienting perspective for developers; expressive epistemologies, or data structures based on subjective human worldviews; morphic semiotics (building on the computer scientist Joseph Goguen's theory of algebraic semiotics); cultural phantasms that influence consensus and reveal other perspectives; computing systems based on cultural models; interaction and expression; and the ways that real-world information is mapped onto, and instantiated by, computational data structures. The concept of phantasmal media, Harrell argues, offers new possibilities for using the computer to understand and improve the human condition through the human capacity to imagine.
  galvanize data science immersive: Threatcasting Brian David Johnson, Cyndi Coon, Natalie Vanatta, 2022-06-01 Impending technological advances will widen an adversary’s attack plane over the next decade. Visualizing what the future will hold, and what new threat vectors could emerge, is a task that traditional planning mechanisms struggle to accomplish given the wide range of potential issues. Understanding and preparing for the future operating environment is the basis of an analytical method known as Threatcasting. It is a method that gives researchers a structured way to envision and plan for risks ten years in the future. Threatcasting uses input from social science, technical research, cultural history, economics, trends, expert interviews, and even a little science fiction to recognize future threats and design potential futures. During this human-centric process, participants brainstorm what actions can be taken to identify, track, disrupt, mitigate, and recover from the possible threats. Specifically, groups explore how to transform the future they desire into reality while avoiding an undesired future. The Threatcasting method also exposes what events could happen that indicate the progression toward an increasingly possible threat landscape. This book begins with an overview of the Threatcasting method with examples and case studies to enhance the academic foundation. Along with end-of-chapter exercises to enhance the reader’s understanding of the concepts, there is also a full project where the reader can conduct a mock Threatcasting on the topic of “the next biological public health crisis.” The second half of the book is designed as a practitioner’s handbook. It has three separate chapters (based on the general size of the Threatcasting group) that walk the reader through how to apply the knowledge from Part I to conduct an actual Threatcasting activity. This book will be useful for a wide audience (from student to practitioner) and will hopefully promote new dialogues across communities and novel developments in the area.
  galvanize data science immersive: Moonwalking with Einstein Joshua Foer, 2011-03-03 The blockbuster phenomenon that charts an amazing journey of the mind while revolutionizing our concept of memory “Highly entertaining.” —Adam Gopnik, The New Yorker “Funny, curious, erudite, and full of useful details about ancient techniques of training memory.” —The Boston Globe An instant bestseller that has now become a classic, Moonwalking with Einstein recounts Joshua Foer's yearlong quest to improve his memory under the tutelage of top mental athletes. He draws on cutting-edge research, a surprising cultural history of remembering, and venerable tricks of the mentalist's trade to transform our understanding of human memory. From the United States Memory Championship to deep within the author's own mind, this is an electrifying work of journalism that reminds us that, in every way that matters, we are the sum of our memories.
  galvanize data science immersive: To Life! Linda Weintraub, 2012-09-01 This title documents the burgeoning eco art movement from A to Z, presenting a panorama of artistic responses to environmental concerns, from Ant Farms anti-consumer antics in the 1970s to Marina Zurkows 2007 animation that anticipates the havoc wreaked upon the planet by global warming.
  galvanize data science immersive: The Emperor of All Maladies Siddhartha Mukherjee, 2011-08-09 Winner of the Pulitzer Prize and a documentary from Ken Burns on PBS, this New York Times bestseller is “an extraordinary achievement” (The New Yorker)—a magnificent, profoundly humane “biography” of cancer—from its first documented appearances thousands of years ago through the epic battles in the twentieth century to cure, control, and conquer it to a radical new understanding of its essence. Physician, researcher, and award-winning science writer, Siddhartha Mukherjee examines cancer with a cellular biologist’s precision, a historian’s perspective, and a biographer’s passion. The result is an astonishingly lucid and eloquent chronicle of a disease humans have lived with—and perished from—for more than five thousand years. The story of cancer is a story of human ingenuity, resilience, and perseverance, but also of hubris, paternalism, and misperception. Mukherjee recounts centuries of discoveries, setbacks, victories, and deaths, told through the eyes of his predecessors and peers, training their wits against an infinitely resourceful adversary that, just three decades ago, was thought to be easily vanquished in an all-out “war against cancer.” The book reads like a literary thriller with cancer as the protagonist. Riveting, urgent, and surprising, The Emperor of All Maladies provides a fascinating glimpse into the future of cancer treatments. It is an illuminating book that provides hope and clarity to those seeking to demystify cancer.
  galvanize data science immersive: Americans and Climate Change Daniel Rhame Abbasi, 2006 Part I of this report is a synthesis that highlights eight selected themes, each of which relates to diagnoses, recommendations, and important lines of debate or inquiry. Part II describes the diagnoses and 39 recommendations from the eight working groups.
  galvanize data science immersive: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
  galvanize data science immersive: The Human Capital Index 2020 Update World Bank, 2021-05-05 Human capital—the knowledge, skills, and health that people accumulate over their lives—is a central driver of sustainable growth, poverty reduction, and successful societies. More human capital is associated with higher earnings for people, higher income for countries, and stronger cohesion in societies. Much of the hard-won human capital gains in many economies over the past decade is at risk of being eroded by the COVID-19 (coronavirus) pandemic. Urgent action is needed to protect these advances, particularly among the poor and vulnerable. Designing the needed interventions, targeting them to achieve the highest effectiveness, and navigating difficult trade-offs make investing in better measurement of human capital now more important than ever. The Human Capital Index (HCI)—launched in 2018 as part of the Human Capital Project—is an international metric that benchmarks the key components of human capital across economies. The HCI is a global effort to accelerate progress toward a world where all children can achieve their full potential. Measuring the human capital that children born today can expect to attain by their 18th birthdays, the HCI highlights how current health and education outcomes shape the productivity of the next generation of workers and underscores the importance of government and societal investments in human capital. The Human Capital Index 2020 Update: Human Capital in the Time of COVID-19 presents the first update of the HCI, using health and education data available as of March 2020. It documents new evidence on trends, examples of successes, and analytical work on the utilization of human capital. The new data—collected before the global onset of COVID-19—can act as a baseline to track its effects on health and education outcomes. The report highlights how better measurement is essential for policy makers to design effective interventions and target support. In the immediate term, investments in better measurement and data use will guide pandemic containment strategies and support for those who are most affected. In the medium term, better curation and use of administrative, survey, and identification data can guide policy choices in an environment of limited fiscal space and competing priorities. In the longer term, the hope is that economies will be able to do more than simply recover lost ground. Ambitious, evidence-driven policy measures in health, education, and social protection can pave the way for today’s children to surpass the human capital achievements and quality of life of the generations that preceded them.
  galvanize data science immersive: Decolonizing Science in Latin American Art Joanna Page , 2021-04-15 Projects that bring the ‘hard’ sciences into art are increasingly being exhibited in galleries and museums across the world. In a surge of publications on the subject, few focus on regions beyond Europe and the Anglophone world. Decolonizing Science in Latin American Art assembles a new corpus of art-science projects by Latin American artists, ranging from big-budget collaborations with NASA and MIT to homegrown experiments in artists’ kitchens. While they draw on recent scientific research, these art projects also ‘decolonize’ science. If increasing knowledge of the natural world has often gone hand-in-hand with our objectification and exploitation of it, the artists studied here emphasize the subjectivity and intelligence of other species, staging new forms of collaboration and co-creativity beyond the human. They design technologies that work with organic processes to promote the health of ecosystems, and seek alternatives to the logics of extractivism and monoculture farming that have caused extensive ecological damage in Latin America. They develop do-it-yourself, open-source, commons-based practices for sharing creative and intellectual property. They establish critical dialogues between Western science and indigenous thought, reconnecting a disembedded, abstracted form of knowledge with the cultural, social, spiritual, and ethical spheres of experience from which it has often been excluded. Decolonizing Science in Latin American Art interrogates how artistic practices may communicate, extend, supplement, and challenge scientific ideas. At the same time, it explores broader questions in the field of art, including the relationship between knowledge, care, and curation; nonhuman agency; art and utility; and changing approaches to participation. It also highlights important contributions by Latin American thinkers to themes of global significance, including the Anthropocene, climate change and environmental justice.
  galvanize data science immersive: Surveillance Valley Yasha Levine, 2018-02-06 The internet is the most effective weapon the government has ever built. In this fascinating book, investigative reporter Yasha Levine uncovers the secret origins of the internet, tracing it back to a Pentagon counterinsurgency surveillance project. A visionary intelligence officer, William Godel, realized that the key to winning the war in Vietnam was not outgunning the enemy, but using new information technology to understand their motives and anticipate their movements. This idea -- using computers to spy on people and groups perceived as a threat, both at home and abroad -- drove ARPA to develop the internet in the 1960s, and continues to be at the heart of the modern internet we all know and use today. As Levine shows, surveillance wasn't something that suddenly appeared on the internet; it was woven into the fabric of the technology. But this isn't just a story about the NSA or other domestic programs run by the government. As the book spins forward in time, Levine examines the private surveillance business that powers tech-industry giants like Google, Facebook, and Amazon, revealing how these companies spy on their users for profit, all while doing double duty as military and intelligence contractors. Levine shows that the military and Silicon Valley are effectively inseparable: a military-digital complex that permeates everything connected to the internet, even coopting and weaponizing the antigovernment privacy movement that sprang up in the wake of Edward Snowden. With deep research, skilled storytelling, and provocative arguments, Surveillance Valley will change the way you think about the news -- and the device on which you read it.
  galvanize data science immersive: Python for Bioinformatics Sebastian Bassi, 2017-08-07 In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.
  galvanize data science immersive: Small Change, Big Gains Thomas H. Stoner Jr., 2013-09-17 This book provides an innovative look at our global energy supply as if it were a single portfolio of assets through which we can generate wealth, while mitigating climate change.
  galvanize data science immersive: Problems of Hope Patrick Bresnihan, Leila Dawney, 2017-11-01 However hopeless we often feel, we are creatures of hope. This collection of short accessible essays explores the ways in which hope is bound up with power in worlds that are composed through imagination, transformation and feeling. Hope is the most precious ingredient of power. The essays do not assume hope to be inherently good or emancipatory. Rather they reflect on how hope can both support and obstruct us in our efforts to make lives more livable, or futures more just. The essays draw on social research, philosophy, literature, music and film to show how hope might re-enchant writing and politics for a post-hopeful age. This is a book for those who want to remain hopeful but find it hard to see how. Contents Introduction: Problems of hope Cranes, Luke Carter On finding hope beyond progress, Leila Dawney Xanadu, Miles Link Hope without a future in Octavia Butler’s Parable of the Sower, Patrick Bresnihan Eagles, Luke Carter Seeking, Claire Blencowe Hope in a minor key, Naomi Millner Hopefully indebted, Sam Kirwan Starlings, Luke Carter Rhythms of hope, Julian Brigstocke Networked hope, Aécio Amaral The Psychonaut’s journey: Race, closure, and hope, Tehseen Noorani Epilogue Further Reading
  galvanize data science immersive: 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.
  galvanize data science immersive: Cities, Culture and Creativity UNESCO, World Bank (the), 2021-05-25 Culture and creativity have untapped potential to deliver social, economic, and spatial benefits for cities and communities. Cultural and creative industries are key drivers of the creative economy and represent important sources of employment, economic growth, and innovation, thus contributing to city competitiveness and sustainability. Through their contribution to urban regeneration and sustainable urban development, cultural and creative industries make cities more attractive places for people to live in and for economic activity to develop. Culture and creativity also contribute to social cohesion at the neighborhood level, enable creative networks to form and advance innovation and growth, and create opportunities for those who are often socially and economically excluded. The ongoing COVID-19 pandemic has had a deep impact on the cultural sector, yet it has also revealed the power of cultural and creative industries as a resource for city recovery and resilience. More generally, cities are hubs of the creative economy and have a critical role to play in harnessing the transformative potential of cultural and creative industries through policies and enabling environments at the local level. 'Cities, Culture, and Creativity' (CCC) provides guiding principles and a CCC Framework, developed by UNESCO and the World Bank, to support cities in unlocking the power of cultural and creative industries for sustainable urban development, city competitiveness, and social inclusion. Drawing from global studies and the experiences of nine diverse cities from across the world, the CCC Framework offers concrete guidance for the range of actors -- city, state, and national governments; creative industry and related private-sector organizations; creatives; culture professionals and civil society-- to harness culture and creativity with a view to boosting their local creative economies and building resilient, inclusive, and dynamic cities.
  galvanize data science immersive: Educating the Net Generation Diana Oblinger, James L. Oblinger, 2005-01-01 This e-book offers an insightful look into the way today's students think about and use technology in their academic and social lives. It will help institutional leaders help their students to become more successful and satisfied.
  galvanize data science immersive: Does Education Pay Off? , 1991
  galvanize data science immersive: Machine Learning Bookcamp Alexey Grigorev, 2021-11-23 The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.
  galvanize data science immersive: Generation Z Goes to College Corey Seemiller, Meghan Grace, 2016-01-19 Say Hello to Your Incoming Class—They're Not Millennials Anymore Generation Z is rapidly replacing Millennials on college campuses. Those born from 1995 through 2010 have different motivations, learning styles, characteristics, skill sets, and social concerns than previous generations. Unlike Millennials, Generation Z students grew up in a recession and are under no illusions about their prospects for employment after college. While skeptical about the cost and value of higher education, they are also entrepreneurial, innovative, and independent learners concerned with effecting social change. Understanding Generation Z's mindset and goals is paramount to supporting, developing, and educating them through higher education. Generation Z Goes to College showcases findings from an in-depth study of over 1,100 Generation Z college students from 15 vastly different U.S. higher education institutions as well as additional studies from youth, market, and education research related to this generation. Authors Corey Seemiller and Meghan Grace provide interpretations, implications, and recommendations for program, process, and curriculum changes that will maximize the educational impact on Generation Z students. Generation Z Goes to College is the first book on how this up-and-coming generation will change higher education.
  galvanize data science immersive: Communicating in Small Groups Steven A. Beebe, John T. Masterson, 2015 ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for each title, including customized versions for individual schools, and registrations are not transferable. In addition, you may need a CourseID, provided by your instructor, to register for and use Pearson's MyLab & Mastering products. Packages Access codes for Pearson's MyLab & Mastering products may not be included when purchasing or renting from companies other than Pearson; check with the seller before completing your purchase. Used or rental books If you rent or purchase a used book with an access code, the access code may have been redeemed previously and you may have to purchase a new access code. Access codes Access codes that are purchased from sellers other than Pearson carry a higher risk of being either the wrong ISBN or a previously redeemed code. Check with the seller prior to purchase. -- Balances the principles of small group communication with real world applications With an emphasis on real world examples, technology, and ethical collaboration, Communicating in Small Groups: Principles and Practices helps readers enhance their performance in groups and teams, while giving them insight into why group and team members communicate as they do. MySearchLab is a part of the Beebe/Masterson program. Research and writing tools, including access to academic journals, help students understand critical thinking in even greater depth. To provide students with flexibility, students can download the eText to a tablet using the free Pearson eText app. 0133815617 / 9780133815610 Communicating in Small Groups: Principles and Practices Plus MySearchLab with eText -- Access Card Package Package consists of: 0205239927 / 9780205239924 MySearchLab with Pearson eText -- Valuepack Access Card 020598083X / 9780205980833 Communicating in Small Groups: Principles and Practices
  galvanize data science immersive: 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
  galvanize data science immersive: Python for Programmers Paul Deitel, Harvey Deitel, 2019-03-15 The professional programmer’s Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter® Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Accompanying code examples are available here: http://ptgmedia.pearsoncmg.com/imprint_downloads/informit/bookreg/9780135224335/9780135224335_examples.zip. Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for more information.
  galvanize data science immersive: The Entrepreneur's Roadmap New York Stock Exchange, 2017-06 Entrepreneur's guide for starting and growing a business to a public listing
  galvanize data science immersive: Computational Thinking Education Siu-Cheung Kong, Harold Abelson, 2019-07-04 This This book is open access under a CC BY 4.0 license.This book offers a comprehensive guide, covering every important aspect of computational thinking education. It provides an in-depth discussion of computational thinking, including the notion of perceiving computational thinking practices as ways of mapping models from the abstraction of data and process structures to natural phenomena. Further, it explores how computational thinking education is implemented in different regions, and how computational thinking is being integrated into subject learning in K-12 education. In closing, it discusses computational thinking from the perspective of STEM education, the use of video games to teach computational thinking, and how computational thinking is helping to transform the quality of the workforce in the textile and apparel industry.
  galvanize data science immersive: Strategic Latency Unleashed Zachary Davis, Frank Gac, Philip Reiner, Christopher Rager, Jennifer Snow, 2021-01-30 The world is being transformed physically and politically. Technology is the handmaiden of much of this change. But since the current sweep of global change is transforming the face of warfare, Special Operations Forces (SOF) must adapt to these circumstances. Fortunately, adaptation is in the SOF DNA. This book examines the changes affecting SOF and offers possible solutions to the complexities that are challenging many long-held assumptions. The chapters explore what has changed, what stays the same, and what it all means for U.S. SOF. The authors are a mix of leading experts in technology, business, policy, intelligence, and geopolitics, partnered with experienced special operators who either cowrote the chapters or reviewed them to ensure accuracy and relevance for SOF. Our goal is to provide insights into the changes around us and generate ideas about how SOF can adapt and succeed in the emerging operational environment.
  galvanize data science immersive: Machine Learning Mastery With Weka Jason Brownlee, 2016-06-23 Machine learning is not just for professors. Weka is a top machine learning platform that provides an easy-to-use graphical interface and state-of-the-art algorithms. In this Ebook, learn exactly how to get started with applied machine learning using the Weka platform.
  galvanize data science immersive: The Minimum You Need to Know about Logic to Work in IT Roland Hughes, 2007 This book is part of aaThe Minimum You Need to Knowaa family of books by Logikal Solutions. As the family expands they will cover an increasing variety of topics. This book is designed to be used as a text book for classes in logic from high school to college level. It should be one of the first courses you have on IT and this should be one of the first books you read when starting in IT. Not only does this book cover flow charting and pseudocode, it teaches the reader to think before they start mapping out the logic to solve a problem. The author of this book is an industry veteran with nearly 20 years in the field. It has been his experience that recent graduates, from any country, are nearly useless at problem solving. If they cannot point, click, and drag, they cannot solve the problem. This book is an attempt to teach them how to solve the problem. An instructoraas guide is available for schools looking to make this book the basis of coursework.
  galvanize data science immersive: The Practice of Art and AI Andreas J. Hirsch, Gerfried Stocker, Markus Jandl, 2022-01-04 Multidisciplinary explorations of AI and its implications for art In this multidisciplinary volume, European ARTificial Intelligence Lab, in partnership with Ars Electronica, considers the incredibly rapid development of Artificial Intelligence in the context of the cyber-arts. Bringing together 13 cultural and six scientific institutions from across Europe, this publication explores the interdisciplinary exchange between art and science and summarizes the accomplishments of the AI Lab since its opening. This guide to the events and exhibitions for this project includes more than 500 reproductions, profiles on featured exhibitors and essays. In keeping with the project's focus on the interplay between art and technology, the book includes QR codes which link the reader to video lectures and other supplementary materials. Artists and researchers include: Eva Smrekar, Eduardo Reck Miranda, Ian Gouldstone, Aarati Akkapeddi, Cecilie Waagner Falkenstrøm, Tega Brain, Sam Lavigne, Hannah Jayanti, Sarah Petkus, Mark J. Koch, Mimi Onuoha, Caroline Sinders, LaJuné McMillian, Victoria Vesna and many more.
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