But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    C. R. Licklider, Doug Engelbart, Bob Taylor, and Alan Kay.The digital revolution did not begin with the teenage millionaires of Silicon Valley, claims Howard Rheingold, but with such early intellectual giants as Charles Babbage, George Boole, and John von Neumann. In a highly engaging style, Rheingold tells the story of what he calls the patriarchs, pioneers, and infonauts of the computer, focusing in particular on such pioneers as J. C. R. Licklider, Doug Engelbart, Bob Taylor, and Alan Kay. Taking the reader step by step from nineteenth-century mathematics to contemporary computing, he introduces a fascinating collection of eccentrics, mavericks, geniuses, and visionaries.The book was originally published in 1985, and Rheingold's attempt to envision computing in the 1990s turns out to have been remarkably prescient. This edition contains an afterword, in which Rheingold interviews some of the pioneers discussed in the book. As an exercise in what he calls retrospective futurism, Rheingold also looks back at how he looked forward.

    With this concise book, you will quickly gain working knowledge of Sinatra and its minimalist approach to building both standalone and modular web applications. Sinatra serves as a lightweight wrapper around Rack middleware, with syntax that maps closely to functions exposed by HTTP verbs, which makes it ideal for web services and APIs. If you have experience building applications with Ruby, you’ll quickly learn language fundamentals and see under-the-hood techniques, with the help of several practical examples. Then you’ll get hands-on experience with Sinatra by building your own blog engine. Learn Sinatra’s core concepts, and get started by building a simple application Create views, manage sessions, and work with Sinatra route definitions Become familiar with the language’s internals, and take a closer look at Rack Use different subclass methods for building flexible and robust architectures Put Sinatra to work: build a blog that takes advantage of service hooks provided by the GitHub API

    The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors

    Thanks to it, you will be able to UNLEASH the full power of your Amazon Echo, Echo Dot and Amazon Tap. AND you will find my email address at the end of the book, so feel free to ask me any questions you might have about Alexa. What is Amazon Echo Dot and Alexa Let me help you figure out what this this exciting technology is all about, so you can enjoy it too! Amazon Echo is a speaker connected to the internet that you can control with your voice. Alexa is the built-in vocal assistant of Amazon Echo. Alexa lets you play music, control your lights, ask for the weather and more. What you will learn: Step-by-step instructions on how to set up your device Get to know about all the things that Amazon Echo can do Get customized News, Traffic and Weather updates Connect your Google Calendar to your device Everything you need to know about Alexa in a single HIGH-QUALITY book Stream music from your favorite audio sources: iPhone, Android, Spotify, Amazon Music, Pandora, iHeartRadio, TuneIn Get ACTIONABLE ADVICE on how to build your smart home Control your lights, TV and room temperature with your voice Explore the complete list of Alexa-enabled devices organized per category Have fun by playing with 500 Easter Eggs Learn How IFTTT and Yonomi help you to better control your home Get to know the 20 most useful Alexa Skills Learn how Amazon Echo was created Written By An Alexa Lover For (future) Alexa Lovers How to troubleshoot your Echo Learn how Alexa works behind the scenes Explore the future of Alexa And much, much more! This is the only Amazon Echo book you will ever need Get your copy today! This book will save you hours figuring out how Echo works. I am sharing all my hacks so you can go from Beginner to Expert in an hour. I wish that upon reading this book, you will realise this exciting times that we live in. That you will see all the possibilities that the Amazon Echo has to offer. The time for innovation is now, and it is up to you to enjoy it now. Through the book, you will come to see Echo for what it is and what it can be. I am exploring in depth numerous topics such as Playing Music, Building your Smart Home, Using Alexa Skills and more. This book will help save you many hours trying to figure out what the Echo can do. Bonus Sign up to my free weekly newsletter to get the best new Alexa Skills in your inbox. Table of Contents 1. Preface 2. The Genesis of Amazon Echo 3. How Does Alexa Work? 4.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With 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: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    Now an internationally recognized scientist at a top U.S. medical school—one of the leading researchers in the field—sheds light on the extraordinary benefits of these natural health superstars. Thanks to an explosion of research in recent years, one thing is clear: probiotics, the healthy bacteria that inhabit the digestive tract, are the body’s silent partners for good health, optimizing the power of the immune system to fight disease and the “bad” germs we fear. But how do they work? And in the face of factors like stress and poor diet, which decrease their numbers, how do you keep your supply well stocked? Here is an up-to-the-minute, highly accessible guide to probiotics and the foods and supplements that contain and support them—many of which may be in your diet already. Discover:The key role of probiotics and prebiotics in restoring healthy balance to our bodies, improving immune system functioning, and curbing inflammationHow to use probiotic foods and supplements to prevent and relieve allergies, inflammatory bowel disease, irritable bowel syndrome, yeast infections, and the negative side effects of antibiotic useNew evidence that probiotics may help fight asthma, cardiovascular disease, breast and colon cancer, autoimmune diseases, chronic fatigue, fibromyalgia—and even obesityNatural sources of prebiotics, the nutrients that help make the digestive tract more hospitable for probiotic bacteriaThe Probiotics Revolution also includes a step-by-step plan for incorporating the many food sources of probiotics and prebiotics into your diet, a complete buyer’s guide to probiotic supplements, and how to introduce probiotics to your family and children.From the Hardcover edition.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Try out more than 1,000 commands to find and get software, monitor system health and security, and access network resources. Then, apply the skills you learn from this book to use and administer desktops and servers running Ubuntu, Debian, and KNOPPIX or any other Linux distribution.

    Welcome to laughing until it hurts while covered in bodily fluids. Welcome to simple math at very high stakes. Welcome to an incredibly inappropriate sense of humor. Welcome to serving people on the most stressful days of their lives. Welcome to putting your hands in places you never imagined they'd be. Welcome to your front row seat to the ballad of life and death. That's not the welcome that this nurse was looking for, but that's the one he got. Irreverent and audacious, this brutally honest memoir covers what it’s like to come of age in an American Hospital. Welcome to a rollicking peak behind the curtain to what medical providers, and the health care system, are truly like.

    The British expected R.101 to spearhead a fleet of imperial airships that would dominate the skies as British naval ships, a century earlier, had ruled the seas. The dream ended when, on its demonstration flight to India, R.101 crashed in France, tragically killing nearly all aboard.Combining meticulous research with superb storytelling, Fatal Flight guides us from the moment the great airship emerged from its giant shed—nearly the largest building in the British Empire—to soar on its first flight, to its last fateful voyage. The full story behind R.101 shows that, although it was a failure, it was nevertheless a supremely imaginative human creation. The technical achievement of creating R.101 reveals the beauty, majesty, and, of course, the sorrow of the human experience.The narrative follows First Officer Noel Atherstone and his crew from the ship’s first test flight in 1929 to its fiery crash on October 5, 1930. It reveals in graphic detail the heroic actions of Atherstone as he battled tremendous obstacles. He fought political pressures to hurry the ship into the air, fended off Britain’s most feted airship pilot, who used his influence to take command of the ship and nearly crashed it, and, a scant two months before departing for India, guided the rebuilding of the ship to correct its faulty design. After this tragic accident, Britain abandoned airships, but R.101 flew again, its scrap melted down and sold to the Zeppelin Company, who used it to create LZ 129, an airship even more mighty than R.101—and better known as the Hindenburg. Set against the backdrop of the British Empire at the height of its power in the early twentieth century,Fatal Flight portrays an extraordinary age in technology, fueled by humankind’s obsession with flight.

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.

    With this book you will learn how to tap into every Kindle Fire feature, including many of the hidden ones not discussed in other books. From setting up your Kindle Page, managing your music, watching movies, and downloading content - this book covers everything. The task based full-color format allows you to quickly and easily find the exact task you want to accomplish and walks you through it in a delightfully concise and visual manner. My Kindle Fire makes it easy for you to:• Master all the basics, fast: reading, playing, watching, browsing, and more• Tweak your Kindle Fire for quicker access and longer battery life• Sample best-seller book chapters for free• Mark up any eBook with highlights, notes, and bookmarks• Convert your personal documents for use on Kindle Fire• Discover Calibre, a powerful eBook management tool• Control even the largest music libraries• Get instant answers from Wikipedia, and from Kindle Fire’s built-in dictionary• Listen to personalized Internet radio stations created just for you• Use your Kindle Fire as a digital photo frame• Prevent unwanted subscription charges• Set up any email account to work on your Kindle Fire• Explore any web content with Amazon’s innovative Silk browser• Use Amazon Cloud to get your stuff anywhere—even if you left your Kindle at home• And much much more…Unlike many other guides which might only briefly mention or skip over some very import Kindle Fire features My Kindle Fire covers everything. Here are just a few of the things you'll find in My Kindle Fire that aren't covered in other guides: • Full coverage of Calibre, a free application for Mac or PC that helps manage your eBook library• A large number of walkthroughs for managing music playlists, including how to use cloud playlists. • How to reinstall multiple apps at once in case you reset your Kindle Fire. • Step-by-step walkthroughs on configuring all types of email accounts. • Coverage on handling attachments in your email application. • Importing contacts from your existing email application or cloud service and how you can export your contacts in order to back them up. • How to use Copy and Paste on the Kindle Fire. • How to use social networking integration with Facebook and others. • Walkthroughs on using the Gallery app, Pandora, Audible, and other popular apps. • Shows you how to access files on other computers in your house right from your Kindle Fire.