The Elements of Statistical Learning: Data Mining, Inference, and Prediction


Trevor Hastie - 2001
    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

Practical SQL: A Beginner's Guide to Storytelling with Data


Anthony DeBarros - 2018
    The book focuses on using SQL to find the story your data tells, with the popular open-source database PostgreSQL and the pgAdmin interface as its primary tools.You'll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from the U.S. Census and other federal and state government agencies. With exercises and real-world examples in each chapter, this book will teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently.You'll learn how to: •Create databases and related tables using your own data •Define the right data types for your information •Aggregate, sort, and filter data to find patterns •Use basic math and advanced statistical functions •Identify errors in data and clean them up •Import and export data using delimited text files •Write queries for geographic information systems (GIS) •Create advanced queries and automate tasks Learning SQL doesn't have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases. This book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.

Deep Learning


Ian Goodfellow - 2016
    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Becoming Human: Our Past, Present and Future


Scientific American - 2013
    

Programming Entity Framework: DbContext


Julia Lerman - 2011
    This concise book shows you how to use the API to perform set operations with the DbSet class, handle change tracking and resolve concurrency conflicts with the Change Tracker API, and validate changes to your data with the Validation API.With DbContext, you’ll be able to query and update data, whether you’re working with individual objects or graphs of objects and their related data. You’ll find numerous C# code samples to help you get started. All you need is experience with Visual Studio and database management basics.Use EF’s query capabilities to retrieve data, and use LINQ to sort and filter dataLearn how to add new data, and change and delete existing dataUse the Change Tracker API to access information EF keeps about the state of entity instancesControl change tracking information of entities in disconnected scenarios, including NTier applicationsValidate data changes before they’re sent to the database, and set up validation rulesBypass EF’s query pipeline and interact directly with the database

Hadoop: The Definitive Guide


Tom White - 2009
    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

Data Science from Scratch: First Principles with Python


Joel Grus - 2015
    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

Now You See It: Simple Visualization Techniques for Quantitative Analysis


Stephen Few - 2009
    Employing a methodology that is primarily learning by example and “thinking with our eyes,” this manual features graphs and practical analytical techniques that can be applied to a broad range of data analysis tools—including the most commonly used Microsoft Excel. This approach is particularly valuable to those who need to make sense of quantitative business data by discerning meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities, and hints about the future. It provides practical skills that are useful to managers at all levels and to those interested in keeping a keen eye on their business.

Kindle Fire HDX User Guide: Newbie to Expert in 2 Hours!


Tom Edwards - 2013
    We still remember the first time we turned on our Kindle Fire! Although it may feel like everybody else already knows how to use their Kindle Fire the truth is they don't. And if this is the first time you've held one in your hands, then we would just like to say..... WE'RE HERE TO HELP!From the Number #1 Amazon Bestselling Authors in Computers and Technology.When we first published our Kindle Fire app review guide - 250+ Best Kindle Fire HD Apps for the New Kindle Fire Owner - we added in a small bonus section which included a few tips and tricks for the new Kindle Fire user. We soon started receiving emails from customers asking for more of the same.Well this easy-to-use guide is our way of welcoming all you new Kindle Fire owners who have just pulled your device from its box for the first time. This short user guide has been written to introduce you to some of the most basic, but essential, elements of using your new handheld computer. This is information that you need to know.This Amazon Kindle e-Book Includes:Navigating your way around the Kindle Fire HDGetting rid of adsDownloading and transferring contentConnecting to social mediaSetting up emailLearning to 'swype'Getting to grips with parental controls

Naked Statistics: Stripping the Dread from the Data


Charles Wheelan - 2012
    How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

Ninja Foodi: The Pressure Cooker that Crisps: Complete Cookbook for Beginners: Your Expert Guide to Pressure Cook, Air Fry, Dehydrate, and More


Kenzie Swanhart - 2018
    Here, in the official Ninja® Foodi™ Complete Cookbook for Beginners, you’ll find easy, flavorful recipes specifically designed for the innovative technology of the Ninja® Foodi™.No matter what you’re in the mood for, there’s a wide range of versatile recipes in Ninja® Foodi™ Complete Cookbook for Beginners. From wholesome “360 Meals” that allow you to fully cook grains, crisp vegetables, and tender proteins all in the same pot, to time-saving “Frozen to Crispy” recipes that allow you to cook frozen food without defrosting it first, the Ninja® Foodi™ Complete Cookbook for Beginners puts tasty, nourishing meals on the table in no time.The ultimate beginner’s guide for using this one-of-a-kind appliance, the Ninja® Foodi™ Complete Cookbook for Beginners includes: 75 quick, tasty, good-for-you recipes that include options not only for breakfast, lunch, and dinner, but also appetizers, breads, desserts, and more Quick-start guidance for using your Ninja® Foodi™ and understanding all of its unique features such as how to pressure cook, air fry, TenderCrisp™, dehydrate, and more Expert tips and tricks that will eliminate the learning curve regardless of your prior culinary experience There is no dinner dilemma that the Ninja® Foodi™ can’t handle. And with the official Ninja® Foodi™ Complete Cookbook for Beginners, there’s no recipe that you can’t cook.

Python for Data Analysis


Wes McKinney - 2011
    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

Mastering Aperture, Shutter Speed, ISO and Exposure


Al Judge - 2013
    You have an opportunity to learn it quickly and easily in just a few hours.</i></h2><br><p>Adjusting APERTURE, DEPTH-OF-FIELD, SHUTTER SPEED, ISO and EXPOSURE will no longer be sources of stress, and your confidence will be greatly enhanced. With very little time and effort you can be well on your way to taking better pictures consistently. </p><br><ul><li>Do your eyes glaze over when people use terms like ISO, Aperture, Shutter Speed, and Exposure?</li><li>Does the term f-stop make your stomach turn?</li><li>Are you enthused about photography but confused by all the technical jargon?</li><li>Would you like to be more consistent with the quality of your images?</li><li>Do you wonder how professional photographers get such great shots?</li></ul><br><h2> Ultimately you will need to understand Exposure and its components Aperture, Shutter Speed, and ISO — also known as the Exposure Triangle — and how they work together if you want to have any control over your results.</h2><br><p><b><i>Mastering Aperture, Shutter Speed, ISO, and Exposure: How They Interact and Affect Each Other </i></b> will painlessly provide help and insight with all these topics and more in just a few hours of your time</p><br><p>Without a guide on your path to better pictures, you run the risk of spending a great deal of time and money heading down the wrong road. Frustration and confusion can easily take the wind from your sails and replace excitement with disappointment. </p><br><p>This guide to EXPOSURE builds a solid foundation of photographic knowledge with easy-to-follow discussions of everything that you need to know in order to create better images with confidence. Every photographic term used in the book is clearly defined and thoroughly explained. All terms are also highlighted by using <b>BOLD CAPS</b> so that you can easily find them again to refresh your memory. </p><br><h2>What reviewers have said about Mastering Aperture......!</h2><br><p><b>Despite this book's rather advanced topics, it is perfect for beginners wanting to learn more.</b> Jeff</p><br><p><b>A great guide for all levels of photography, well written and illustrated!!!</b> Albert</p><br><p><b>This is another great book of Al's. He does a wonderful job at explaining all the needed information to better understand photography. Very easy to understand and lots of pointers.</b> DJ</p><br><p><b>As I am about to commence a photography diploma this book has come in handy as a warm up for me.</b> Craig </p><br><h2> By the time you finish reading this book, you will be well on your way to Mastering Aperture, Shutter Speed, ISO and Exposure </h2><br><p>To learn about Al's other photography books, please go to his author page at: http://www.amazon.com/author/al.judge </p><br><h2>Why spend any more time “Shooting in the Dark?” Scroll up and grab a copy today for less than the cost of a cup of coffee.</h2>

Jumping into C++


Alex Allain - 2013
    As a professional C++ developer and former Harvard teaching fellow, I know what you need to know to be a great C++ programmer, and I know how to teach it, one step at a time. I know where people struggle, and why, and how to make it clear. I cover every step of the programming process, including:Getting the tools you need to program and how to use them*Basic language feature like variables, loops and functions*How to go from an idea to code*A clear, understandable explanation of pointers*Strings, file IO, arrays, references*Classes and advanced class design*C++-specific programming patterns*Object oriented programming*Data structures and the standard template library (STL)Key concepts are reinforced with quizzes and over 75 practice problems.

Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites


Matthew A. Russell - 2011
    You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google