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 practical guide shows you how to be productive with this tool quickly, whether you're a developer deploying code to production or a system administrator looking for a better automation solution.Author Lorin Hochstein shows you how to write playbooks (Ansible's configuration management scripts), manage remote servers, and explore the tool's real power: built-in declarative modules. You'll discover that Ansible has the functionality you need and the simplicity you desire.Understand how Ansible differs from other configuration management systemsUse the YAML file format to write your own playbooksLearn Ansible's support for variables and factsWork with a complete example to deploy a non-trivial applicationUse roles to simplify and reuse playbooksMake playbooks run faster with ssh multiplexing, pipelining, and parallelismDeploy applications to Amazon EC2 and other cloud platformsUse Ansible to create Docker images and deploy Docker containers

    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

    It is very readable and the stress many beginners face about memorizing arcane syntax typically presented by other programming languages will not affect you at all. Conversely, you will be able to concentrate on learning concepts and paradigms of programming. This book shall introduce you to an easy way to learn Python in just 7 days and in this time, be able to complete your own projects! By reading the book and implementing what you learn herein, you will realize just why major institutions like NASA, Google, Mozilla, Yahoo, Dropbox, IBM, Facebook and many others prefer to use python in their core products, services and business processes. Let

    Missile trajectories. Cornering dynamics in speeding cars. By applying the laws of physics, you can realistically model nearly everything in games that bounces around, flies, rolls, slides, or isn't sitting still, to create compelling, believable content for computer games, simulations, and animation. "Physics for Game Developers" serves as the starting point for those who want to enrich games with physics-based realism.Part one is a mechanics primer that reviews basic concepts and addresses aspects of rigid body dynamics, including kinematics, force, and kinetics. Part two applies these concepts to specific real-world problems, such as projectiles, boats, airplanes, and cars. Part three introduces real-time simulations and shows how they apply to computer games. Many specific game elements stand to benefit from the use of real physics, including: The trajectory of rockets and missiles, including the effects of fuel burn offThe collision of objects such as billiard ballsThe stability of cars racing around tight curvesThe dynamics of boats and other waterborne vehiclesThe flight path of a baseball after being struck by a batThe flight characteristics of airplanesYou don't need to be a physics expert to learn from "Physics for Game Developers, " but the author does assume you know basic college-level classical physics. You should also be proficient in trigonometry, vector and matrix math (reference formulas and identities are included in the appendixes), and college-level calculus, including integration and differentiation of explicit functions. Although the thrust of the book involves physics principles and algorithms, it should be noted that the examples are written in standard C and use Windows API functions.

    Work at your own pace through a series of lessons and practical exercises, and then assess your skills with practice tests on CD—featuring multiple, customizable testing options.Maximize your performance on the exam by learning how to:Create database objectsWork with dataModify dataTroubleshoot and optimize queriesYou also get an exam discount voucher—making this book an exceptional value and a great career investment.

    Indeed, that's what computers are for. You can enlist your own computer to automate all of your project's repetitive tasks, ranging from individual builds and running unit tests through to full product release, customer deployment, and monitoring the system.Many teams try to do these tasks by hand. That's usually a really bad idea: people just aren't as good at repetitive tasks as machines. You run the risk of doing it differently the one time it matters, on one machine but not another, or doing it just plain wrong. But the computer can do these tasks for you the same way, time after time, without bothering you. You can transform these labor-intensive, boring and potentially risky chores into automatic, background processes that just work.In this eagerly anticipated book, you'll find a variety of popular, open-source tools to help automate your project. With this book, you will learn: How to make your build processes accurate, reliable, fast, and easy. How to build complex systems at the touch of a button. How to build, test, and release software automatically, with no human intervention. Technologies and tools available for automation: which to use and when. Tricks and tips from the masters (do you know how to have your cell phone tell you that your build just failed?) You'll find easy-to-implement recipes to automate your Java project, using the same popular style as the rest of our Jolt Productivity Award-winning Starter Kit books. Armed with plenty of examples and concrete, pragmatic advice, you'll find it's easy to get started and reap the benefits of modern software development. You can begin to enjoy pragmatic, automatic, unattended software production that's reliable and accurate every time.

    While learning these technologies, you will discover coding practices such as writing code that works on multiple browsers including mobile devices, how to use AJAX frameworks to add interactivity to your pages, and how to ensure your pages meet accessible requirements.Packed with real-world examples, the book not only teaches you how to write Web sites using XHTML, CSS and JavaScript, but it also teaches you design principles that help you create attractive web sites and practical advice on how to make web pages more usable. In addition, special checklists and appendices review key topics and provide helpful references that re-enforce the basics you've learned.Serves as an ideal beginners guide to writing web pages using XHTML Explains how to use CSS to make pages more appealing and add interactivity to pages using JavaScript and AJAX frameworks Share advice on design principles and how to make pages more attractive and offers practical help with usability and accessibility Features checklists and appendices that review key topics This introductory guide is essential reading for getting started with using XHTML, CSS and JavaScript to create exciting and compelling Web sites.Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

    But instead of spending hours and hours trying to develop your own answers, now you can find out how the pros do it! Game Programming Gems is a hands-on, comprehensive resource packed with a variety of game programming algorithms written by experts from the game industry and edited by Mark DeLoura, former software engineering lead for Nintendo of America, Inc. and now the newly appointed editor-in-chief of Game Developer magazine. From animation and artificial intelligence to Z-buffering, lighting calculations, weather effects, curved surfaces, mutliple layer Internet gaming, to music and sound effects, all of the major techniques needed to develop a competitive game engine are covered. Game Programming Gems is written in a style accessible to individuals with a range of expertise levels. All of the source code for each algorithm is included and can be used by advanced programmers immediately. For aspiring programmers, there is a detailed tutorial to work through before attempting the code, and suggestions for possible modifications and optimizations are included as well.

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will:Solve a particular coding problem or improve on the performance of an existing solutionQuickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to useGet algorithmic solutions in C, C++, Java, and Ruby with implementation tipsLearn the expected performance of an algorithm, and the conditions it needs to perform at its bestDiscover the impact that similar design decisions have on different algorithmsLearn advanced data structures to improve the efficiency of algorithmsWith Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.

    The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it.In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go.Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

    With this book’s extensively revised second edition, you’ll focus on Android tools and programming essentials, including best practices for using Android 4 APIs. If you’re experienced with Java or Objective-C, you’ll gain the knowledge necessary for building well-engineered applications.Programming Android is organized into four parts:Part One helps programmers with some Java or iOS experience get off to a fast start with the Android SDK and Android programming basics.Part Two delves into the Android framework, focusing on user interface and graphics class hierarchies, concurrency, and databases. It’s a solid foundation for understanding of how the most important parts of an Android application work.Part Three features code skeletons and patterns for accelerating the development of apps that use web data and Android 4 user interface conventions and APIs.Part Four delivers practical coverage of Android’s multimedia, search, location, sensor, and account APIs, plus the Native Development Kit, enabling developers to add advanced capabilities.This updated edition of Programming Android focuses on the knowledge and developer priorities that are essential for successful Android development projects.

    Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.

    Displaying extraordinary creativity and programming virtuosity, Alexandrescu offers a cutting-edge approach to design that unites design patterns, generic programming, and C++, enabling programmers to achieve expressive, flexible, and highly reusable code. This book introduces the concept of generic components--reusable design templates that produce boilerplate code for compiler consumption--all within C++. Generic components enable an easier and more seamless transition from design to application code, generate code that better expresses the original design intention, and support the reuse of design structures with minimal recoding. The author describes the specific C++ techniques and features that are used in building generic components and goes on to implement industrial strength generic components for real-world applications. Recurring issues that C++ developers face in their day-to-day activity are discussed in depth and implemented in a generic way. These include: Policy-based design for flexibility Partial template specialization Typelists--powerful type manipulation structures Patterns such as Visitor, Singleton, Command, and Factories Multi-method engines For each generic component, the book presents the fundamental problems and design options, and finally implements a generic solution.