This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.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. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    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.

    It's about learning to eat properly for your health." -Vitor Belfort, UFC two-time world champion"Mike Dolce's the best in the business."-Chael Sonnen, UFC world title contender"Mike Dolce's knowledge of nutrition and strength & conditioning has led him to be one of the most highly sought-after coaches in the sport." -Joshua Carey, Bleacher Report"You can learn a lot from this man right here." -Ariel Helwani, AOL's MMAFighting.comABOUT THE DOLCE DIET: LIVING LEANCalled "the patron saint of weight cutting," Mike Dolce has coordinated the high-profile weight loss for many of the world's top athletes, including...* Quinton "Rampage" Jackson, UFC / Pride FC world champion* Vitor "The Phenom" Belfort, UFC two-time world champion* Thiago "Pitbull" Alves, UFC world title contender* Chael Sonnen WEC / UFC world title contender* Gray "Bully" Maynard, UFC world title contender* Nate "Rock" Quarry, UFC world title contender* Mike "Quicksand" Pyle, WEC world champion* Jay "Thorobred" Hieron, IFL world championAs well as fan favorites...* Michael "The Count" Bisping, The Ultimate Fighter 3 winner* Jake "Juggernaut" Ellenberger, UFC veteran* Ed "Shortfuse" Herman, The Ultimate Fighter 3 runner-up* Chris "The Crippler" Leben, UFC veteran* Duane "BANG" Ludwig, UFC & K-1 veteranand many more!For the first time in print, Mike Dolce shares the same the principles, recipes, and strength-training workouts he uses in MMA's elite fight camps and how they can be used by YOU!INSIDE you will learn:* Recipes used in MMA's top fight camps with gluten-free & vegan options* Easy to follow sample meal plans with gluten-free & vegan options* Strength & Conditioning exercises with instructions & photos* Workout plans used by today's top athletesWHAT PEOPLE ARE SAYING ABOUT THE DOLCE DIETThe Dolce Diet, three words about Living Lean: 1. Simple 2. Inspirational 3. Effective. Thank you, Mike Dolce! You've made staying in shape easy! ~STEWART M. The Dolce Diet, Love it! My Little-Boy-2-B has been on it for 5.5 months! This diet is truly amazing for moms pre & post baby! Yes, The DolceDiet is prego friendly! Plenty of the RIGHT kind of food that tastes great! ~THE H2H WAITRESSStarted two weeks ago. Lost 13 pounds so far. Yea! Love the recipes! So do my kids! Thank you! ~DAWN H.Body fat down 4% in 2 months?! Yessss! #LIVING LEAN ~MOLLY C.The Dolce Diet, started 410, down 50 lbs. so far. ~ JOSH W.The Dolce Diet, 13 lbs. lost in 4 weeks! People are asking what I'm doing...Telling them LIVING LEAN! ~MIKE S.Real talk! The Dolce Diet is the Einstein, da Vinci and Jesus of losing weight all wrapped up in one...gluten free wrap that is. ~MIKEY F.Another 5 (lbs. lost) on The Dolce Diet. 25 pounds down in 2 weeks, 100 to go! #LivingLean! ~JOHN P.

    The Windows Command Line Beginner's Guide gives users new to the Windows command line an overview of the Command Prompt, from simple tasks to network configuration.In the Guide, you'll learn how to:-Manage the Command Prompt.-Copy & paste from the Windows Command Prompt.-Create batch files.-Remotely manage Windows machines from the command line.-Manage disks, partitions, and volumes.-Set an IP address and configure other network settings.-Set and manage NTFS and file sharing permissions.-Customize and modify the Command Prompt.-Create and manage file shares.-Copy, move, and delete files and directories from the command line.-Manage PDF files and office documents from the command line.-And many other topics.

    Her website, sherrilynkenyon.com, tells us that her books are stand-alone reads that do not have to be read in order. But it also mentions inside jokes that will only be caught when the books are read in the order they were released. This information is available on the author's website, sherrilynkenyon.com. If, like me, you'd like to have the list on your kindle where you can pop it open just like your other kindle books instead of logging on to your laptop or PC, you will find this list handy. Hopefully you have the Kindle Unlimited subscription and can download it for free. If not, you'll have to decide if the convenience is worth a buck. This is a title list only. In reading order. No portions of the books mentioned have been reproduced here. No copyright infringement is intended. Just to avoid any misunderstandings about copyright, according to the United States Copyright Office, “Copyright law does not protect names, titles, or short phrases or expressions.” (copyright.gov, circular 34). I hope you find this made-for-kindle list as helpful as I do in deciding which of Ms. Kenyon's books to purchase and enjoy next.

    Readers will discover how to groom a parakeet, recognize the symptoms of illness, and keep a parakeet safe from other pets. They will also see how to teach a parakeet to talk, understand parakeet behavior, and find an avian veterinarian.

    She founded the Facebook group Extreme Couponing and Bargains UK (the second largest Facebook group in the world) and is on TikTok, Youtube and Instagram helping as many people as possible to save money too.This book contains all her best hacks and tips to save money and make money - simple, life-changing ideas for everyone.Holly has included her favourite hacks from the Extreme Couponing and Bargains UK community too, who inspired her to write this book. And has asked all her money-saving expert friends to contribute tips too.All the costly moments of everyday life are included, from supermarket shops to kids parties - even special occasions like weddings and Christmas.Discover lots of fun ways to get saving, find the bargains and make your money go further.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    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.

    Design patterns are time-tested solutions to recurring problems, letting the designer build programs on solutions that have already proved effective Provides developers with more than a dozen ASP.NET examples showing standard design patterns and how using them helpsbuild a richer understanding of ASP.NET architecture, as well as better ASP.NET applications Builds a solid understanding of ASP.NET architecture that can be used over and over again in many projects Covers ASP.NET code to implement many standard patterns including Model-View-Controller (MVC), ETL, Master-Master Snapshot, Master-Slave-Snapshot, Facade, Singleton, Factory, Single Access Point, Roles, Limited View, observer, page controller, common communication patterns, and more

    The Authors Discuss The Mathematical Theory In Detail And Then Provide The Geometric Interpretation Necessary To Make 3D Math Intuitive. Working C++ Classes Illustrate How To Put The Techniques Into Practice, And Exercises At The End Of Each Chapter Help Reinforce The Concepts. This Book Explains Basic Concepts Such As Vectors, Coordinate Spaces, Matrices, Transformations, Euler Angles, Homogenous Coordinates, Geometric Primitives, Intersection Tests, And Triangle Meshes. It Discusses Orientation In 3D, Including Thorough Coverage Of Quaternions And A Comparison Of The Advantages And Disadvantages Of Different Representation Techniques. The Text Describes Working C++ Classes For Mathematical And Geometric Entities And Several Different Matrix Classes, Each Tailored To Specific Geometric Tasks. Also Included Are Complete Derivations For All The Primitive Transformation Matrices.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    The presentation is never awkward or dry, as it sometimes is in other "modern" textbooks; it is as unconventional as one has come to expect from the author. The book contains about 350 well placed and instructive problems, which cover a considerable part of the subject. All in all, this is an excellent work, of equally high value for both student and teacher." Zentralblatt f�r Mathematik

    During our journey we will explore stories from Babylon, Greece, Ireland, Ethiopia, and various other cultures to fill in the missing pieces to one of the biggest mysteries on our planet. This 2nd Edition includes 40+ hours of additional audio and video content for your enjoyment. Make sure you download a free QR code scanner for your smart phone or tablet so you can take full advantage of the features in this book.

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora