Found inside – Page iiIntroduction to React teaches you React, the JavaScript framework created by developers at Facebook, to solve the problem of building complex user interfaces in a consistent and maintainable way. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. Found inside – Page 1This book will introduce you to JavaScript's power and idiosyncrasies and guide you through the key features of the language and its tools and libraries. Fuzzing is often described as a “black box software testing technique. Found inside – Page 1This book is the "Hello, World" tutorial for building products, technologies, and teams in a startup environment. The New Kingmakers documents the rise of the developer class, and provides strategies for companies to adapt to the new technology landscape. Found insideWith this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas ... Found inside – Page 111Students submit a project proposal after the first midterm exam. ... and the specialization wraps up with an extended capstone project. What others in the trenches say about The Pragmatic Programmer... “The cool thing about this book is that it’s great for keeping the programming process fresh. This guide shows how they can be used to plan programmes and modules, improve feedback to students, assess students validly and review teaching."--Publisher's website. Professionals working in this field will also find this book valuable. Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn ... This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and ... 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. This book will get you there. About the Book Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. Found insideAbout the Book Get Programming with JavaScript Next introduces you to the new features included in the ES2015-and-later JavaScript releases. You'll learn example by example in 34 short lessons, each designed to drive home a specific skill. Found insideThe definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to ... The book introduces neural networks with TensorFlow, runs through the main applications, covers two working example apps, and then dives into TF and cloudin production, TF mobile, and using TensorFlow with AutoML. "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"-- If you are a penetration testing team leader or individual who wishes to challenge yourself or your friends in the creation of penetration testing assault courses, this is the book for you. 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 ... Found insideData Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re ... This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. You'll especially appreciate the easy-to-follow discussions, illuminating diagrams, and carefully explained code! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. This book is ideal for security engineers and data scientists alike. This book introduces machine learning methods in finance. This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. While the text is biased against complex equations, a mathematical background is needed for advanced topics. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Found insideReinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python. Found inside – Page 1This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and ... Found insideThis book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the ... Found insideThe environment grows with readers as they master the material in the book until it supports a full-fledged language for the whole spectrum of programming tasks. This second edition has been completely revised. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Presents an introduction to the new programming language for the Java Platform. With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Key Features ... Found inside – Page 300Rhodes et al. demonstrated how their capstone course promotes a student ... education include a great deal more than learning to code (Philip et al. 2013). Diving deep into the JavaScript language to show you how to write beautiful, effective code, this book uses extensive examples and immerses you in code from the start, while exercises and full-chapter projects give you hands-on experience ... This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. Found inside – Page 1Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Found inside – Page 456Our current BDMA course focuses on data mining and machine learning algorithms ... Our capstone course to be designed will be titled Big Data and Machine ... This book constitutes extended, revised and selected papers from the 9th International Conference on Cloud Computing and Services Science, CLOSER 2019, held in Heraklion, Greece, in May 2019.The 11 papers presented in this volume were ... Found insideThis book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision ... Found insideThis book is part of the Standard Ebooks project, which produces free public domain ebooks. You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Found insideToday ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. 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. Et al applying them and Options offers a vision for the emerging of... To the new programming language for the Java Platform true artificial intelligence in your analysis... Short lessons, each designed to drive home a specific skill specialization wraps up with extended., a mathematical background is needed for advanced topics is ideal for engineers... Solving real-world data-centric problems than learning to code ( Philip et al the print book includes a eBook! 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