Found insideThis book presents high-quality, peer-reviewed papers from the FICR International Conference on Rising Threats in Expert Applications and Solutions 2020, held at IIS University Jaipur, Rajasthan, India, on January 17-19, 2020. Found insideNow with a new afterword by Bryan Caplan, this explosive book argues that the primary function of education is not to enhance students' skills but to signal the qualities of a good employee. Found inside – Page iiiThis is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. Found insideWhat you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement ... This book introduces the reader to the latest innovations in fields such as artificial intelligence, systems biology or surgery, and gives advice on what new technologies to consider for becoming a market leader of tomorrow. If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected. Found insideWhile Robotic Process Automation (RPA) has been around for about 20 years, it has hit an inflection point because of the convergence of cloud computing, big data and AI. This book shows you how to leverage RPA effectively in your company to ... Found inside – Page iiiInside this book, you will learn how to: bull; bull;Work with key database components--tables, rows, records, columns, and fields bull;Store and retrieve data bull;Perform advanced data manipulation bull;Control SQL*Plus bull;Apply Oracle ... Found inside – Page iThis book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Found insideThis book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies Found inside – Page 1With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data ... Found inside – Page 1This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. Found insideThis book is published open access under a CC BY 4.0 license. Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. Found insideThis book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. Found insideDemystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from ... Found inside – Page 1The recommendations offered in Capturing Change in Science, Technology, and Innovation are intended to serve as the basis for a strategic program of work that will enhance NCSES's ability to produce indicators that capture change in science ... Deep Learning with PyTorch teaches you to create deep learning and neural network systems with PyTorch. This practical book gets you to work right away building a tumor image classifier from scratch. Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Found insideThis book constitutes the proceedings of the 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, held in Porto, Portugal, in September 2018. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. Found insideThis book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one. This book presents a new model, the competency framework, for students, innovators, entrepreneurs, managers, and anyone who wants to better understand the dynamic world of innovation and entrepreneurship. Found inside – Page 1About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Load, wrangle, and analyze your data using the world's most powerful statistical programming language About This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics ... Found insideIn The Cult of Smart, educator and outspoken leftist Fredrik deBoer exposes this omission as the central flaw of our entire society, which has created and perpetuated an unjust class structure based on intellectual ability. "This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"-- Found insideIn this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ... Found insideIn this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. Found insideThe book's five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Found insidePractitioners in these and related fields will find this book perfect for self-study as well. Found insideThe second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. Do you want to use R to tell stories? This book was written for you—whether you already know some R or have never coded before. Most R texts focus only on programming or statistical theory. These are then brought together by implementing deep reinforcement learning for automated trading. This book will serve as a continuing reference for implementing deep learning models to build investment strategies. "This book is not just about learning to program; although you will learn to code. Examine the latest technological advancements in building a scalable machine learning model with Big Data using R. This book shows you how to work with a machine learning algorithm and use it to build a ML model from raw data. Found insideBecome an efficient data scientist with R About This Book Explore the R language from basic types and data structures to advanced topics Learn how to tackle programming problems and explore both functional and object-oriented programming ... Found insideLearn how people break websites and how you can, too. Real-World Bug Hunting is the premier field guide to finding software bugs. Presents case studies and instructions on how to solve data analysis problems using Python. Found insideThis guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of ... Found inside – Page iWho This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. The Digital Economy Report 2019 on "Value creation and capture: Implications for developing countries" takes stock of recent trends in the global digital landscape and discusses the development and policy implications of data and digital ... In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Found insideA Professor at the End of Time tells one professor’s story in the context of the rapid reconfiguration of higher education going on now, and analyzes what the job included before the supernova of technological innovation, the general ... The Data Science Handbook is a curated collection of 25 candid, honest and insightful interviews conducted with some of the world's top data scientists.In this book, you'll hear how the co-creator of the term 'data scientist' thinks about ... Found insideHow do Bitcoin and its block chain actually work? 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