The R language is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    In the Mastering Emacs ebook you will learn the answers to all the concepts that take weeks, months or even years to truly learn, all in one place.“Emacs is such a hard editor to learn”But why is it so hard to learn? As it turns out, it's almost always the same handful of issues that everyone faces.If you have tried to learn Emacs you will have struggled with the same problems everyone faces, and few tutorials to see you through it.I have dedicated the first half of the book to explaining the essence of Emacs — and in doing so, how to overcome these issues:Memorizing Emacs’s keys: You will learn Emacs one key at a time, starting with the arrow keys. To feel productive in Emacs, it’s important you start on an equal footing — without too many new concepts and keys to memorize. Each chapter will introduce more keys and concepts so you can learn at your own pace. Discovering new modes and features: Emacs is a self-documenting editor, and I will teach you how to use the apropos, info, and describe system to discover new modes and features, or help you find things you forgot! Customizing Emacs: You don’t have to learn Emacs Lisp to alter a lot of Emacs’s functionality. Most changes you want to make are possible using Emacs’s Customize interface and I will show you how to use it efficiently. Understanding the terminology: Emacs is so old it predates almost every other editor and all modern user interfaces. I have an entire chapter dedicated to the unique terminology in Emacs; how it is different from other editors, and what that means to you.

    In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.

    This practical guide shows you how to design and maintain infrastructure capable of managing the full lifecycle of these implementations.Engineers Justin Garrison (Walt Disney Animation Studios) and Kris Nova (Dies, Inc.) reveal hard-earned lessons on architecting infrastructure for massive scale and best in class monitoring, alerting, and troubleshooting. The authors focus on Cloud Native Computing Foundation projects and explain where each is crucial to managing modern applications.Understand the fundamentals of cloud native application design, and how it differs from traditional application designLearn how cloud native infrastructure is different from traditional infrastructureManage application lifecycles running on cloud native infrastructure, using Kubernetes for application deployment, scaling, and upgradesMonitor cloud native infrastructure and applications, using fluentd for logging and prometheus + graphana for visualizing dataDebug running applications and learn how to trace a distributed application and dig deep into a running system with OpenTracing

    Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

    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.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    Agile is increasingly popular with software teams because the ones that have gone agile often talk about the great results they get. The software they build is better, which makes a big difference to them and their users. Not only that, but when agile teams are effective, they have a much better time at work! Things are more relaxed, and the working environment is a lot more enjoyable.Head First Agile is a brain-friendly guide to understanding agile concepts and ideas. Here s what you ll find inside:The agile mindset, what an agile methodology is, and why agile methodologies that seem so different can still all be agileScrum, and how it can help you build better, more valuable software, and make your team and your users happierXP, and how its focus on code and programming can help you and your team build better systemsLean and Kanban, and how they can help your whole team get better every dayWe have two goals for Head First Agile. First and foremost, we want you to learn agile: what it is, and how it can help you build better software and improve your team. But we also are focused on our readers looking to pass the PMI-ACP certification, so not only does the book have 100% coverage of the material for the PMI-ACP exam, it also includes end-of-chapter exam questions, a complete exam study guide, exam tips, and a full-length practice PMI-ACP exam everything that you need to pass the exam.So while Head First Agile is useful for developers, project managers, and others who want to prepare for and pass the PMI-ACP certification exam, this unique book is also valuable for software team members (including developers) who don't necessarily need to pass the PMI-ACP certification exam, but want to learn about agile and how it can help them.Based on the latest research in cognitive science and learning theory, this book uses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works."

    The authors have extensive experience both managing data analysts and conducting their own data analyses, and have carefully observed what produces coherent results and what fails to produce useful insights into data. This book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    Where to begin? Head First Android Development will help you get your first application up and running in no time with the Android SDK and Eclipse plug-in. You'll learn how to design for devices with a variety of different screen sizes and resolutions, along with mastering core programming and design principles that will make your app stand out.Whether you're a seasoned iPhone developer who wants to jump into the the Android Market, or someone with previous programming skills but no mobile apps in your resume, this book offers a complete learning experience for creating eye-catching, top-selling Android applications.You'll learn how to:Install the Android SDK and Eclipse plug-in and get started building appsAdd buttons, edit text fields, and build your own navigation options in the Android menuCustomize the look of your app with theming and adding image resourcesUse Android's content provider mechanism to add images and contact information to an app, and establish permissions for their useWork with the Android devices' camera, GPS, and accelerometerExperiment with different Android emulator configurations to simulate different devices with a variety of screen sizesOptimize, test, and distribute your application in the Android MarketWe think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Android Development uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    Instead of surrendering to these common problems, let Head First Software Development guide you through the best practices of software development. Before you know it, those failed projects will be a thing of the past. With its unique visually rich format, this book pulls together the hard lessons learned by expert software developers over the years. You'll gain essential information about each step of the software development lifecycle -- requirements, design, coding, testing, implementing, and maintenance -- and understand why and how different development processes work. This book is for you if you are:Tired of your customers assuming you're psychic. You'll learn not only how to get good requirements, but how to make sure you're always building the software that customers want (even when they're not sure themselves) Wondering when the other 15 programmers you need to get your project done on time are going to show up. You'll learn how some very simple scheduling and prioritizing will revolutionize your success rate in developing software. Confused about being rational, agile, or a tester. You'll learn not only about the various development methodologies out there, but how to choose a solution that's right for your project. Confused because the way you ran your last project worked so well, but failed miserably this time around. You'll learn how to tackle each project individually, combine lessons you've learned on previous projects with cutting-edge development techniques, and end up with great software on every project.Head First Software Development is here to help you learn in a way that your brain likes... and you'll have a blast along the way. Why pick up hundreds of boring books on the philosophy of this approach or the formal techniques required for that one? Stick with Head First Software Development, and your projects will succeed like never before. Go on, get started... you'll learn and have fun. We promise.