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| elvtr course cost product management: Traversing the Traction Gap Bruce Cleveland, Wildcat Venture Partners, 2019-02-21 Traction. Startups Need It. Learn How To Get It. Vision, groundbreaking ideas, total commitment, and boundless enthusiasm characterize most startups, but they require capital to go from promising product to scalable business. More than 80 percent of all early-stage startups fail. Most of them can build a product, but the vast majority stumble when it comes time to take those products to market due to poor “market engineering” skills. Traversing the Traction Gap exposes the reasons behind that scary failure rate and provides a prescriptive how-to guide, focused specifically on market engineering techniques, so startups can succeed. The go-to-market hurdle is insurmountable to many startups. Just when they most need to establish a foothold in the market, they run short on time and money. This is the Traction Gap, that period of time introducing a new product into the marketplace and being able to scale it during a rapidly closing window of opportunity. Traversing the Traction Gap is a practical guidebook for navigating the tumultuous early life of a startup. Based on real-life examples, the advice from Cleveland and the members of the Wildcat Venture Partners team provides a roadmap and metrics for succeeding where others have failed. |
| elvtr course cost product management: Healthcare Data Analytics Chandan K. Reddy, Charu C. Aggarwal, 2015-06-23 At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available |
| elvtr course cost product management: e-Learning Ecologies Bill Cope, Mary Kalantzis, 2017-02-17 e-Learning Ecologies explores transformations in the patterns of pedagogy that accompany e-learning—the use of computing devices that mediate or supplement the relationships between learners and teachers—to present and assess learnable content, to provide spaces where students do their work, and to mediate peer-to-peer interactions. Written by the members of the new learning research group, this textbook suggests that e-learning ecologies may play a key part in shifting the systems of modern education, even as technology itself is pedagogically neutral. The chapters in this book aim to create an analytical framework with which to differentiate those aspects of educational technology that reproduce old pedagogical relations from those that are genuinely innovative and generative of new kinds of learning. Featuring case studies from elementary schools, colleges, and universities on the practicalities of new learning environments, e-Learning Ecologies elucidates the role of new technologies of knowledge representation and communication in bringing about change to educational institutions. |
| elvtr course cost product management: Designing Evolvable Web APIs with ASP.NET Glenn Block, Pablo Cibraro, Pedro Felix, Howard Dierking, Darrel Miller, 2014-03-13 Design and build Web APIs for a broad range of clients—including browsers and mobile devices—that can adapt to change over time. This practical, hands-on guide takes you through the theory and tools you need to build evolvable HTTP services with Microsoft’s ASP.NET Web API framework. In the process, you’ll learn how design and implement a real-world Web API. Ideal for experienced .NET developers, this book’s sections on basic Web API theory and design also apply to developers who work with other development stacks such as Java, Ruby, PHP, and Node. Dig into HTTP essentials, as well as API development concepts and styles Learn ASP.NET Web API fundamentals, including the lifecycle of a request as it travels through the framework Design the Issue Tracker API example, exploring topics such as hypermedia support with collection+json Use behavioral-driven development with ASP.NET Web API to implement and enhance the application Explore techniques for building clients that are resilient to change, and make it easy to consume hypermedia APIs Get a comprehensive reference on how ASP.NET Web API works under the hood, including security and testability |
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| elvtr course cost product management: Data Science for Healthcare Sergio Consoli, Diego Reforgiato Recupero, Milan Petković, 2019-02-23 This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book. |
| elvtr course cost product management: Agile at Work: Building Your Agile Team , 2015 Agile is becoming the preferred project management approach for fast-moving projects. At the heart of any agile project lies an agile team. In this course, the first in the Agile at Work series, expert Doug Rose uses a sample project to show how to build your agile team. A team with an agile mindset is self-organized, collaborative, and accountable. He also outlines the common pitfalls inherent in the implementation: new teams need to watch for confusing their roles and understand the challenges with managing self-organized groups. |
| elvtr course cost product management: Boundless Love Javier Llerena, Christina Llerena, 2019-09-08 Do you want a marriage that lasts well beyond the national average of seven years and exceeds your expectations of love and intimacy? Do you aspire to have a relationship that brings you closer to God, builds you up, and encourages you to be a better person? In Boundless Love: Healing Your Marriage Before It Begins, down to earth book authors and married couple Javier and Christina Llerena share their expertise from facilitating over 1,000 individuals preparing for marriage. In an intimate account of their relationship--one that has been transformed through faith--they reveal life-changing lessons they have learned as they almost ended their marriage after their second child. Whether you are single, dating, engaged, or married, Boundless Love provides you with a spiritually-based path with clear cut steps on: How to navigate modern-day dating and create a faith-filled courtship How to create healthy boundaries with yourself, your partner, friends, and family members How to stop your childhood from sabotaging your relationship and find opportunities for growth How to leverage your faith to make optimal life decisions with prayer and spiritual discernment How to surrender one's need to be right to trust one's spouse and God's will. If you want to build your marriage upon faith and like helpful examples, detailed action steps, with a touch of humor, you will love Christina and Javier's powerful path to putting faith at the center of your marriage. Boundless Love kickstarts your faith and reveals that what God has in store for your marriage is far better than anything you can create or imagine on our own. Read this book and unlock the healing power of faith in your relationship today! |
| elvtr course cost product management: Coalfields of New Mexico Geological Survey (U.S.), Morris W. Green, James W. Mytton, Dorothy T. Sandberg, Nancy K. Gardner, Laura H. Biewick, Lewis W. Boger, Antoinette L. Medlin, C. L. Pillmore, Frank Wayne Campbell, Gretchen K. Hoffman, Frank Edward Kottlowski, Brian W. Arkell, 1992 |
| elvtr course cost product management: An Introduction to Rehabilitation Engineering Rory A Cooper, Hisaichi Ohnabe, Douglas A. Hobson, 2006-12-26 This resource focuses on the principles, modeling, standards, devices, and technologies of rehabilitation engineering and assistive technology. It describes numerous design models and processes, including participatory action design and service delivery models. The book also discusses the components of devices such as cushions, wheelchairs, prostheses, orthoses, hearing aids, and TTYs. The contributors assess industry standards and explore innovative technology aids, such as sensors, robot-assisted therapy, and speech recognition software. The text contains a set of learning objectives and study questions in each chapter as well as a list of definitions at the end of the book. |
| elvtr course cost product management: Archimate(r) 3.1 Specification Van Haren Publishing, 2020-02 The ArchiMate(R) Specification, a standard of The Open Group, defines an open and independent modeling language for Enterprise Architecture that is supported by different tool vendors and consulting firms. The ArchiMate language enables Enterprise Architects to describe, analyze, and visualize the relationships among business domains in an unambiguous way. This book is the official specification of the ArchiMate 3.1 modeling language from The Open Group. This edition of the standard includes a number of corrections, clarifications, and improvements to the previous edition, as well as several additions. The main changes between Version 3.0.1 and Version 3.1 of the ArchiMate Specification are listed below. In addition to these changes, various other minor improvements in definitions and other wording have been made: Introduced a new strategy element: value stream Added an optional directed notation for the association relationship Improved the organization of the metamodel and associated figures Further improved and formalized the derivation of relationships The intended audience is threefold: 1.Enterprise Architecture practitioners, such as architects (e.g., business, application, information, process, infrastructure, and, obviously, enterprise architects), senior and operational management, project leaders, and anyone committed to work within the reference framework defined by the Enterprise Architecture. 2.Those who intend to implement the ArchiMate language in a software tool; they will find a complete and detailed description of the language in this book. - The academic community, on which we rely for amending and improving the language, based on state-of-the-art research results in the Enterprise Architecture field. |
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| elvtr course cost product management: Essential Statistics for Non-STEM Data Analysts Rongpeng Li, 2020-11-12 Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data using Python programming Key FeaturesWork your way through the entire data analysis pipeline with statistics concerns in mind to make reasonable decisionsUnderstand how various data science algorithms functionBuild a solid foundation in statistics for data science and machine learning using Python-based examplesBook Description Statistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines. This book is a detailed guide covering the math and various statistical methods required for undertaking data science tasks. The book starts by showing you how to preprocess data and inspect distributions and correlations from a statistical perspective. You’ll then get to grips with the fundamentals of statistical analysis and apply its concepts to real-world datasets. As you advance, you’ll find out how statistical concepts emerge from different stages of data science pipelines, understand the summary of datasets in the language of statistics, and use it to build a solid foundation for robust data products such as explanatory models and predictive models. Once you’ve uncovered the working mechanism of data science algorithms, you’ll cover essential concepts for efficient data collection, cleaning, mining, visualization, and analysis. Finally, you’ll implement statistical methods in key machine learning tasks such as classification, regression, tree-based methods, and ensemble learning. By the end of this Essential Statistics for Non-STEM Data Analysts book, you’ll have learned how to build and present a self-contained, statistics-backed data product to meet your business goals. What you will learnFind out how to grab and load data into an analysis environmentPerform descriptive analysis to extract meaningful summaries from dataDiscover probability, parameter estimation, hypothesis tests, and experiment design best practicesGet to grips with resampling and bootstrapping in PythonDelve into statistical tests with variance analysis, time series analysis, and A/B test examplesUnderstand the statistics behind popular machine learning algorithmsAnswer questions on statistics for data scientist interviewsWho this book is for This book is an entry-level guide for data science enthusiasts, data analysts, and anyone starting out in the field of data science and looking to learn the essential statistical concepts with the help of simple explanations and examples. If you’re a developer or student with a non-mathematical background, you’ll find this book useful. Working knowledge of the Python programming language is required. |
| elvtr course cost product management: Nurse Peggy Anderson, 1990-05 Records the daily thoughts and feelings of a nurse in a large hospital as she tries to balance her complex, often conflicting responsibilities to doctors, patients, and to herself. |
| elvtr course cost product management: New Jewish Feminism Rabbi Elyse Goldstein, 2012-06-28 Jewish Feminism: What Have We Accomplished? What Is Still to Be Done? “When you are in the middle of the revolution you can’t really plan the next steps ahead. But now we can. The book is intended to open up a dialogue between the early Jewish feminist pioneers and the young women shaping Judaism today.... Read it, use it, debate it, ponder it.” —from the Introduction This empowering anthology looks at the growth and accomplishments of Jewish feminism and what that means for Jewish women today and tomorrow. It features the voices of women from every area of Jewish life—the Reform, Reconstructionist, Conservative, Orthodox and Jewish Renewal movements; rabbis, congregational leaders, artists, writers, community service professionals, academics, and chaplains, from the United States, Canada, and Israel—addressing the important issues that concern Jewish women: Women and Theology Women, Ritual and Torah Women and the Synagogue Women in Israel Gender, Sexuality and Age Women and the Denominations Leadership and Social Justice |
| elvtr course cost product management: Knowledge and Strategy Michael H. Zack, 1999 This is the first knowledge book in the Resources for the Knowledge-Based Economy Readers' series to link the two hot topics of knowledge and strategy. The book centers around the concept of treating organizational knowledge as a valuable strategy asset. Knowledge strategy is a natural extension of the historical development of business strategy in general. The book includes seminal articles on the subject as well as an introduction written by Michael Zack. Links together knowledge and strategy Seminal articles |
| elvtr course cost product management: Learning Deep Learning Magnus Ekman, 2021-07-19 NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals. -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us. -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| elvtr course cost product management: Hands-On Data Analysis with Pandas Stefanie Molin, 2019-07-26 Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling in PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning (ML) algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsUse pandas to solve common data representation and analysis problemsBuild Python scripts, modules, and packages for reusable analysis codeWho this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial. |
| elvtr course cost product management: What's New in TensorFlow 2.0 Ajay Baranwal, Alizishaan Khatri, Tanish Baranwal, 2019-08-12 Get to grips with key structural changes in TensorFlow 2.0 Key FeaturesExplore TF Keras APIs and strategies to run GPUs, TPUs, and compatible APIs across the TensorFlow ecosystemLearn and implement best practices for building data ingestion pipelines using TF 2.0 APIsMigrate your existing code from TensorFlow 1.x to TensorFlow 2.0 seamlesslyBook Description TensorFlow is an end-to-end machine learning platform for experts as well as beginners, and its new version, TensorFlow 2.0 (TF 2.0), improves its simplicity and ease of use. This book will help you understand and utilize the latest TensorFlow features. What's New in TensorFlow 2.0 starts by focusing on advanced concepts such as the new TensorFlow Keras APIs, eager execution, and efficient distribution strategies that help you to run your machine learning models on multiple GPUs and TPUs. The book then takes you through the process of building data ingestion and training pipelines, and it provides recommendations and best practices for feeding data to models created using the new tf.keras API. You'll explore the process of building an inference pipeline using TF Serving and other multi-platform deployments before moving on to explore the newly released AIY, which is essentially do-it-yourself AI. This book delves into the core APIs to help you build unified convolutional and recurrent layers and use TensorBoard to visualize deep learning models using what-if analysis. By the end of the book, you'll have learned about compatibility between TF 2.0 and TF 1.x and be able to migrate to TF 2.0 smoothly. What you will learnImplement tf.keras APIs in TF 2.0 to build, train, and deploy production-grade modelsBuild models with Keras integration and eager executionExplore distribution strategies to run models on GPUs and TPUsPerform what-if analysis with TensorBoard across a variety of modelsDiscover Vision Kit, Voice Kit, and the Edge TPU for model deploymentsBuild complex input data pipelines for ingesting large training datasetsWho this book is for If you’re a data scientist, machine learning practitioner, deep learning researcher, or AI enthusiast who wants to migrate code to TensorFlow 2.0 and explore the latest features of TensorFlow 2.0, this book is for you. Prior experience with TensorFlow and Python programming is necessary to understand the concepts covered in the book. |
| elvtr course cost product management: Learning Apache Drill Charles Givre, Paul Rogers, 2018-11-02 Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as HBase, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster. In this practical book, Drill committers Charles Givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you’ll learn how Drill helps you analyze data more effectively to drive down time to insight. Use Drill to clean, prepare, and summarize delimited data for further analysis Query file types including logfiles, Parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL Connect to Drill programmatically using a variety of languages Use Drill even with challenging or ambiguous file formats Perform sophisticated analysis by extending Drill’s functionality with user-defined functions Facilitate data analysis for network security, image metadata, and machine learning |
| elvtr course cost product management: Python Natural Language Processing Cookbook Zhenya Antić, 2021-03-19 Get to grips with solving real-world NLP problems, such as dependency parsing, information extraction, topic modeling, and text data visualization Key Features Analyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensim Implement common and not-so-common linguistic processing tasks using Python libraries Overcome the common challenges faced while implementing NLP pipelines Book DescriptionPython is the most widely used language for natural language processing (NLP) thanks to its extensive tools and libraries for analyzing text and extracting computer-usable data. This book will take you through a range of techniques for text processing, from basics such as parsing the parts of speech to complex topics such as topic modeling, text classification, and visualization. Starting with an overview of NLP, the book presents recipes for dividing text into sentences, stemming and lemmatization, removing stopwords, and parts of speech tagging to help you to prepare your data. You’ll then learn ways of extracting and representing grammatical information, such as dependency parsing and anaphora resolution, discover different ways of representing the semantics using bag-of-words, TF-IDF, word embeddings, and BERT, and develop skills for text classification using keywords, SVMs, LSTMs, and other techniques. As you advance, you’ll also see how to extract information from text, implement unsupervised and supervised techniques for topic modeling, and perform topic modeling of short texts, such as tweets. Additionally, the book shows you how to develop chatbots using NLTK and Rasa and visualize text data. By the end of this NLP book, you’ll have developed the skills to use a powerful set of tools for text processing.What you will learn Become well-versed with basic and advanced NLP techniques in Python Represent grammatical information in text using spaCy, and semantic information using bag-of-words, TF-IDF, and word embeddings Perform text classification using different methods, including SVMs and LSTMs Explore different techniques for topic modeling such as K-means, LDA, NMF, and BERT Work with visualization techniques such as NER and word clouds for different NLP tools Build a basic chatbot using NLTK and Rasa Extract information from text using regular expression techniques and statistical and deep learning tools Who this book is for This book is for data scientists and professionals who want to learn how to work with text. Intermediate knowledge of Python will help you to make the most out of this book. If you are an NLP practitioner, this book will serve as a code reference when working on your projects. |
| elvtr course cost product management: In Defense of Religious Liberty David Novak, 2009 David Novak works his way through the sources of Jewish revelation and the many strands of philosophy to inquire whether a civil society can reasonably claim to be founded in a manner that withstands absolutist tyrannies. He notes that it is not within politics itself that the foundation of political good sense is found. It is found in the prior relation of citizens to God which a polity accepts as good but not of its own making. It is a most valuable effort to have these ideas spelled out so clearly and forcefully. -- James V. Schall, S.J. Georgetown University This is the serious and thoughtful conservative work on law and religion that people who are not conservatives should read, and grapple with. Such people will find Novak''s arguments by turns illuminating and exasperating, and they will fight with the book, as I did, but they will learn a great deal in the process, and the sort of respectful engagement with opposing positions for which Novak has always stood in his career is what he richly deserves to get. -- Martha C. Nussbaum Ernst Freund Distinguished Service Professor of Law and Ethics, Law, Philosophy, and Divinity, University of Chicago Through the analysis of the books of Genesis and Exodus, Novak confronts the central claim of secularists that religion is somehow an enemy to human rights. . . . It is Novak''s great achievement to lay out the necessity for a secular policy to acknowledge the need for religious belief, even as he challenges secularists to return to return to their own premises. --Touchstone Perhaps the most striking and distinctive aspect of In Defense of Religious Liberty is Novak''s consistent, almost dogged, insistence that religion is not private, personal, or individual. . . . This work is a powerful and provocative defense of what Thomas Jefferson called our nation''s boldest experiment in religious libery. -- First Things Novak continues his monumental effort to demonstrate the relevance of Jewish texts and traditions for contemporary political thought...He deserves a wider audience for his argument for the liberty of religious communities to influence the public square...Novak relies upon a concept of natural law in which philosophy and the Jewish tradition are able to meet...He constructs a stunning defense of religious liberty, albeit one that ultimately reads the tradition from a thoroughly modern perspective. --The Review of Politics A thought provoking examination of religion and democracy...In fact, the primacy of divine lawis the best foundation for a secular and multicultural democracy, Novak concludes. --Catholic Library World In Defense of Religious Liberty contains David Novak''s vigorous--and paradoxical--argument that the primacy of divine law is the best foundation for a secular, multicultural democracy. Novak presents his claim, which will astound both liberal and conservative advocates of democracy, in political, philosophical, and theological terms. He shows how the universal norms of divine law are knowable as natural law, that they are the best formulations of the human rights of life, liberty, and the pursuit of happiness, and that their assertion includes an explicit recognition of God as cosmic lawgiver. Furthermore, Novak maintains that the seemingly disparate ideas of divine command, natural law, and human rights can be integrated into one overall political theory. Novak reveals this integration at work in the classical texts of his own Jewish tradition, as well as in the canonical philosophical tradition of the West, from Plato to the Stoics to Grotius to Kant. He also convincingly makes the case that those who reject any legitimate role for religion in discussions of public morality inevitably substitute arbitrary human power for divine command, arbitrary positive law for natural law, and arbitrary governmental entitlements for human rights that exist prior to the establishment of the state. Novak concludes that religious traditions like Judaism, precisely because they incorporate the doctrines of God the cosmic lawgiver, natural law, and human rights, provide the most coherent ontological foundation for democracy in today''s world. |
| elvtr course cost product management: Foundations for Analytics with Python Clinton W. Brownley, 2016-08-16 If you’re like many of Excel’s 750 million users, you want to do more with your data—like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in different formats—by using Python. After author Clinton Brownley takes you through Python basics, you’ll be able to write simple scripts for processing data in spreadsheets as well as databases. You’ll also learn how to use several Python modules for parsing files, grouping data, and producing statistics. No programming experience is necessary. Create and run your own Python scripts by learning basic syntax Use Python’s csv module to read and parse CSV files Read multiple Excel worksheets and workbooks with the xlrd module Perform database operations in MySQL or with the mysqlclient module Create Python applications to find specific records, group data, and parse text files Build statistical graphs and plots with matplotlib, pandas, ggplot, and seaborn Produce summary statistics, and estimate regression and classification models Schedule your scripts to run automatically in both Windows and Mac environments |
| elvtr course cost product management: Two Day International Conference on Data Science and Information Ecosystem’21 Dr.M.Thangaraj, Dr.K.S.Gomathi , |
| elvtr course cost product management: Knowledge Graphs Mayank Kejriwal, Craig A. Knoblock, Pedro Szekely, 2021-03-30 A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods. |
| elvtr course cost product management: Own the A.I. Revolution: Unlock Your Artificial Intelligence Strategy to Disrupt Your Competition Neil Sahota, Michael Ashley, 2019-05-24 Disrupt your industry, boost profitability, and grow your business with a powerful A.I. strategy.Artificial Intelligence (A.I.) is on the verge of disrupting every domain of human existence. What does that mean for your business? Everything. Building on the power of A.I. is the factor that will determine success or failure in the very near future—and this in-depth guide from the man who designed the A.I. system that famously won Jeopardy provides everything you need to be a leader in this revolution.Own the A.I. Revolution provides a future-forward look at A.I.—how it will look in the coming years, the countless business opportunities it will offer, the risks that come with it—and delivers the knowledge you need to navigate it all in real and practical ways. You’ll learn how to:•Find the right off-the-shelf A.I. solutions for your needs•Perform a cost/benefit analysis of implementing A.I. into your business strategy•Train and test A.I. before fully committing•Assemble superior teams to steer your A.I. future•Ensure you remain current and ahead of the curveYou’ll also find interviews with today’s top experts and A.I. thought leaders on the exciting ways organizations are already transforming themselves through this revolutionary technology.A.I. sounds scary to some, but the best business leaders see it as an opportunity—as a way not only to drive profits and outpace the competition, but to build value for customers and make the world a better place. It’s time to face our brave new A.I.-driven world—and make sure you Own the A.I. Revolution! |
| elvtr course cost product management: Mind Movers Diane Hart, 1986 Reproducible assignments in math, science, language arts, social studies, and fine art help students establish good homework habits. |
| elvtr course cost product management: The Complete Idiot's Guide to Breaking Bad Habits Suzanne LeVert, Gary R. McClain, 2000-12-01 Offers advice on and strategies for breaking such bad habits as smoking, alcohol, lying, teeth grinding, over-spending, compulsive cleaning, and chronic procrastination. |
| elvtr course cost product management: Software Product Management Essentials Alyssa S. Dver, 2003 In an economy where efficiency and delivery are key, Software Product Management Essentials is required reading for any software product manager. This hands-on guide will help new product managers sift through the numerous tasks and responsibilities involved in this pinnacle job. The book is loaded with tips and best practices to help even experienced product managers optimize their time and effectiveness. The book focuses on the unique challenges of being a Product Manager in a small to mid-sized software company. It provides a framework for the role of the Product Manager in an environment where there are few resources available to help in tackling the many crucial tasks needed for a quality, on-time delivery of software. Whether you are already a Product Manager or considering a new career in product management, Software Product Management Essentials details a day-in-the-life experience of a PM with both the glory and challenges one faces in this role. Engineers, marketing personnel, quality assurance teams, technical writers, and anyone involved in the product delivery process will find this book extremely useful right away in optimizing the day-to-day interactions across a smaller software organization.Emphasizing that code is only part of the overall software product, Software Product Management Essentials stresses the importance of championing a product. Critical topics covered in the book include the product delivery process, beta testing, launching a software product, and software pricing. An entire chapter is dedicated to the issues of expanding the business internationally and the issues a Product Manager must consider before and during expansion. Numerous templates are provided to fast track the Product Manager's work including a sample non-disclosure agreement, product delivery checklist, and beta test agreement and summary. |
| elvtr course cost product management: Personalized Machine Learning Julian McAuley, 2022-02-03 Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications. |
| elvtr course cost product management: The Book of Afformations® Noah St. John, 2013-08-19 Did you know that asking a new kind of question can immediately change your life? One morning in 1997, college student Noah St. John was in the shower when he asked himself a question that changed his life: Why are we trying to change our lives saying statements we don’t believe . . . when the human mind responds automatically to something even more powerful? That’s when he invented the stunningly simple yet amazingly effective method he named Afformations—a method that’s since helped tens of thousands of people around the world to attract more money, lose hundreds of pounds, find their soul mates, grow their businesses, and dramatically improve their lives, with just four simple steps. The Book of Afformations isn’t just another book on abundance. It’s a proven, step-by-step guidebook to living the life of your dreams. Inside this book, you’ll discover: • What the Belief Gap is and why it’s keeping you stuck • How a struggling insurance salesman increased his income by 560 percent in less than a year—and found the love of his life—using this method • How a 13-year-old girl cured her chronic insomnia using this simple technique—in just one night • What they told you about the Law of Attraction that’s just flat-out wrong • How to quit smoking and overcome depression without drugs or therapy • The 2 most effective questions of all time, and the 1 question you should never ask • How to create instant superstar performance in yourself and everyone in your organization • And that’s just the beginning . . . Are you ready to join the Afformations Revolution? |
| elvtr course cost product management: R for Everyone Jared P. Lander, 2017-06-13 Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available. |
| elvtr course cost product management: Data-Driven Security Jay Jacobs, Bob Rudis, 2014-02-24 Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards. |
| elvtr course cost product management: The Pivot Lori Michele Leavitt, 2017-07-31 Great leaders orchestrate change to generate extraordinary momentum, and to never stall. The Pivot introduces four stages of a well-orchestrated Pivot, and identifies six Key Indicators to track, starting now, as you position for a performance breakthrough. |
| elvtr course cost product management: Digital Product Management, Technology and Practice: Interdisciplinary Perspectives Strader, Troy J., 2010-09-30 This book covers a wide range of digital product management issues and offers some insight into real-world practice and research findings on the technical, operational, and strategic challenges that face digital product managers and researchers now and in the next several decades--Provided by publisher. |
| elvtr course cost product management: Multi-objective Decision Analysis Clinton W. Brownley, 2013-03-28 Whether managing strategy, operations or products, knowing how to make the best decision in a complex, uncertain business environment is difficult. You might be faced with multiple, competing objectives, which means making trade-offs. To complicate matters, any uncertainty makes it hard to explicitly understand how different objectives will impact potential outcomes. This book will help you face these problems. It provides a decision analysis framework implemented as a simple spreadsheet tool. This multi-objective decision analysis framework helps you to measure trade-offs among objectives and incorporate uncertainties and risk preferences. With this book, you will be able to identify what information is needed to make a decision, define how that information should be combined, and, finally, provide quantifiable evidence to clearly communicate and justify the decision. The process involves minimal overhead and is perfect for busy professionals who need a simple, structured process for making, tracking, and communicating decisions. This process makes decision making more efficient by focusing only on information and factors that are well-defined, measureable, and relevant to the decision at hand. The framework requires clear characterization of a decision, ensuring that it can be traced and is consistent with the intended objectives and organizational values. Using this structured decision-making framework, anyone can consistently make better decisions to gain competitive and strategic advantage. |
| elvtr course cost product management: Deep Learning from Scratch Seth Weidman, 2019-09-09 With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework |
| elvtr course cost product management: How Algorithms Create and Prevent Fake News Noah Giansiracusa, 2021 From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning--especially when it comes to discerning the truth and differentiating fact from fiction. This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias - which gets amplified in harmful data feedback loops. Don't be afraid: with this book you'll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope. . |
| elvtr course cost product management: Product Strategy and Management Michael John Baker, Susan J. Hart, 1998 This is a review and analysis of the issues involved in managing products through their life cycle. The work has a managerial orientation and will be ideal for students of marketing, business studies and product development courses. |
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