Fundamentals of Biostatistics with CD-Rom.

    But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your work

    

    It describes 11 interpreters and 2 compilers, including very recent techniques of interpretation and compilation. The book is in two parts. The first starts from a simple evaluation function and enriches it with multiple name spaces, continuations and side-effects with commented variants, while at the same time the language used to define these features is reduced to a simple lambda-calculus. Denotational semantics is then naturally introduced. The second part focuses more on implementation techniques and discusses precompilation for fast interpretation: threaded code or bytecode; compilation towards C. Some extensions are also described such as dynamic evaluation, reflection, macros and objects. This will become the new standard reference for people wanting to know more about the Lisp family of languages: how they work, how they are implemented, what their variants are and why such variants exist. The full code is supplied (and also available over the Net). A large bibliography is given as well as a considerable number of exercises. Thus it may also be used by students to accompany second courses on Lisp or Scheme.

    If you're a business or IT professional, this short hands-on guide teaches you how to pull and transform data with SQL in significant ways. You will quickly master the fundamentals of SQL and learn how to create your own databases.Author Thomas Nield provides exercises throughout the book to help you practice your newfound SQL skills at home, without having to use a database server environment. Not only will you learn how to use key SQL statements to find and manipulate your data, but you'll also discover how to efficiently design and manage databases to meet your needs.You'll also learn how to:Explore relational databases, including lightweight and centralized modelsUse SQLite and SQLiteStudio to create lightweight databases in minutesQuery and transform data in meaningful ways by using SELECT, WHERE, GROUP BY, and ORDER BYJoin tables to get a more complete view of your business dataBuild your own tables and centralized databases by using normalized design principlesManage data by learning how to INSERT, DELETE, and UPDATE records

    The books also provides a companion web site that provides the toold and materials necessary to build the hardware and software.

    Old-style system administrators may be disappearing in the face of automation and cloud computing, but operations have become more significant than ever. As this O'Reilly Radar Report explains, we're moving into a more complex arrangement known as "DevOps."Mike Loukides, O'Reilly's VP of Content Strategy, provides an incisive look into this new world of operations, where IT specialists are becoming part of the development team. In an environment with thousands of servers, these specialists now write the code that maintains the infrastructure. Even applications that run in the cloud have to be resilient and fault tolerant, need to be monitored, and must adjust to huge swings in load. That was underscored by Amazon's EBS outage last year.From the discussions at O'Reilly's Velocity Conference, it's evident that many operations specialists are quickly adapting to the DevOps reality. But as a whole, the industry has just scratched the surface. This report tells you why.

    The Text Was Designed To Familiarize Students With The Foundations And Principles Of Computer Science And To Strengthen The Students' Ability To Carry Out Formal And Rigorous Mathematical Arguments. In The New Fourth Edition, Author Peter Linz Has Offered A Straightforward, Uncomplicated Treatment Of Formal Languages And Automata And Avoids Excessive Mathematical Detail So That Students May Focus On And Understand The Underlying Principles. In An Effort To Further The Accessibility And Comprehension Of The Text, The Author Has Added New Illustrative Examples Throughout.

    However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    Amazingly, the story unveiled in it is true.In the world of math, the Poincaré Conjecture was a holy grail. Decade after decade the theorem that informs how we understand the shape of the universe defied every effort to prove it. Now, after more than a century, an eccentric Russian recluse has found the solution to one of the seven greatest math problems of our time, earning the right to claim the first one-million-dollar Millennium math prize.George Szpiro begins his masterfully told story in 1904 when Frenchman Henri Poincaré formulated a conjecture about a seemingly simple problem. Imagine an ant crawling around on a large surface. How would it know whether the surface is a flat plane, a round sphere, or a bagel- shaped object? The ant would need to lift off into space to observe the object. How could you prove the shape was spherical without actually seeing it? Simply, this is what Poincaré sought to solve.In fact, Poincaré thought he had solved it back at the turn of the twentieth century, but soon realized his mistake. After four more years' work, he gave up. Across the generations from China to Texas, great minds stalked the solution in the wilds of higher dimensions. Among them was Grigory Perelman, a mysterious Russian who seems to have stepped out of a Dostoyevsky novel. Living in near poverty with his mother, he has refused all prizes and academic appointments, and rarely talks to anyone, including fellow mathematicians. It seemed he had lost the race in 2002, when the conjecture was widely but, again, falsely reported as solved. A year later, Perelman dropped three papers onto the Internet that not only proved the Poincaré Conjecture but enlightened the universe of higher dimensions, solving an array of even more mind-bending math with implications that will take an age to unravel. After years of review, his proof has just won him a Fields Medal--the 'Nobel of math'--awarded only once every four years. With no interest in fame, he refused to attend the ceremony, did not accept the medal, and stayed home to watch television.Perelman is a St. Petersburg hero, devoted to an ascetic life of the mind. The story of the enigma in the shape of space that he cracked is part history, part math, and a fascinating tale of the most abstract kind of creativity.

    Haskell emerged in the last decade as a standard for lazy functional programming, a programming style where arguments are evaluated only when the value is actually needed. Haskell is a marvellous demonstration tool for logic and maths because its functional character allows implementations to remain very close to the concepts that get implemented, while the laziness permits smooth handling of infinite data structures.This book does not assume the reader to have previous experience with either programming or construction of formal proofs, but acquaintance with mathematical notation, at the level of secondary school mathematics is presumed. Everything one needs to know about mathematical reasoning or programming is explained as we go along. After proper digestion of the material in this book the reader will be able to write interesting programs, reason about their correctness, and document them in a clear fashion. The reader will also have learned how to set up mathematical proofs in a structured way, and how to read and digest mathematical proofs written by others.

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

    The Reactive Application model addresses these demands through new patterns designed to "react" effectively to user and system events, changes in load, competition for shared system resources, and unanticipated failures. Although reactive design patterns can be implemented using standard enterprise development tools, you best realize the benefits when you pair them with a functional programming language like Scala and an Actor-based concurrency system like Akka.Reactive Design Patterns is a clearly-written guide for building event-driven distributed systems that are resilient, responsive, and scalable. Written by the authors of the Reactive Manifesto, this book teaches you to apply reactive design principles to the real problems of distributed application development. You'll discover technologies and paradigms that can be used to build reactive applications including Akka and other actor-based systems, functional programming, replication and distribution, and implementation techniques such as futures, iteratees, and reactive streams. While the book presents concrete examples in Scala, Java, JavaScript, and Erlang, the primary goal is to introduce patterns and best practices that you can use to apply reactive principles to common problems you'll face when building distributed systems.WHAT'S INSIDE* Discover best practices and patterns for building responsive applications* Build applications that can withstand hardware or software failure at any level* Patterns for fault tolerance, scalability, and responsiveness* Maximize multicore hardware using asynchronous and event-driven solutions* Scale applications under tremendous loadReaders should be familiar with a standard programming language like Java, C++ or C# and be comfortable with the basics of distributed systems. Software engineers and architects will learn how to avoid common pitfalls and apply patterns for solving day-to-day problems in a fault-tolerant and scalable way to maximize their application's responsiveness to users and clients. Project leaders and CTOs will gain a deeper understanding of the philosophy behind resilience and scalability in distributed systems, as well as their limitations, challenges and benefits.