Book picks similar to
Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI by Darren Cook
data-science
ebook
humble-bundle
non-fiction
Programming Scala: Scalability = Functional Programming + Objects
Dean Wampler - 2009
With this book, you'll discover why Scala is ideal for highly scalable, component-based applications that support concurrency and distribution.Programming Scala clearly explains the advantages of Scala as a JVM language. You'll learn how to leverage the wealth of Java class libraries to meet the practical needs of enterprise and Internet projects more easily. Packed with code examples, this book provides useful information on Scala's command-line tools, third-party tools, libraries, and available language-aware plugins for editors and IDEs.Learn how Scala's succinct and flexible code helps you program fasterDiscover the notable improvements Scala offers over Java's object modelGet a concise overview of functional programming, and learn how Scala's support for it offers a better approach to concurrencyKnow how to use mixin composition with traits, pattern matching, concurrency with Actors, and other essential featuresTake advantage of Scala's built-in support for XMLLearn how to develop domain-specific languagesUnderstand the basics for designing test-driven Scala applications
Secrets and Lies: Digital Security in a Networked World
Bruce Schneier - 2000
Identity Theft. Corporate Espionage. National secrets compromised. Can anyone promise security in our digital world?The man who introduced cryptography to the boardroom says no. But in this fascinating read, he shows us how to come closer by developing security measures in terms of context, tools, and strategy. Security is a process, not a product – one that system administrators and corporate executives alike must understand to survive.This edition updated with new information about post-9/11 security.
Introducing Elixir: Getting Started in Functional Programming
Simon St.Laurent - 2013
If you're new to Elixir, its functional style can seem difficult, but with help from this hands-on introduction, you'll scale the learning curve and discover how enjoyable, powerful, and fun this language can be. Elixir combines the robust functional programming of Erlang with an approach that looks more like Ruby and reaches toward metaprogramming with powerful macro features.Authors Simon St. Laurent and J. David Eisenberg show you how to write simple Elixir programs by teaching you one skill at a time. You’ll learn about pattern matching, recursion, message passing, process-oriented programming, and establishing pathways for data rather than telling it where to go. By the end of your journey, you’ll understand why Elixir is ideal for concurrency and resilience.* Get comfortable with IEx, Elixir's command line interface* Become familiar with Elixir’s basic structures by working with numbers* Discover atoms, pattern matching, and guards: the foundations of your program structure* Delve into the heart of Elixir processing with recursion, strings, lists, and higher-order functions* Create processes, send messages among them, and apply pattern matching to incoming messages* Store and manipulate structured data with Erlang Term * Storage (ETS) and the Mnesia database* Build resilient applications with the Open Telecom Platform (OTP)* Define macros with Elixir's meta-programming tools.
Cryptography Engineering: Design Principles and Practical Applications
Niels Ferguson - 2010
Cryptography is vital to keeping information safe, in an era when the formula to do so becomes more and more challenging. Written by a team of world-renowned cryptography experts, this essential guide is the definitive introduction to all major areas of cryptography: message security, key negotiation, and key management. You'll learn how to think like a cryptographer. You'll discover techniques for building cryptography into products from the start and you'll examine the many technical changes in the field.After a basic overview of cryptography and what it means today, this indispensable resource covers such topics as block ciphers, block modes, hash functions, encryption modes, message authentication codes, implementation issues, negotiation protocols, and more. Helpful examples and hands-on exercises enhance your understanding of the multi-faceted field of cryptography.An author team of internationally recognized cryptography experts updates you on vital topics in the field of cryptography Shows you how to build cryptography into products from the start Examines updates and changes to cryptography Includes coverage on key servers, message security, authentication codes, new standards, block ciphers, message authentication codes, and more Cryptography Engineering gets you up to speed in the ever-evolving field of cryptography.
Practical Reverse Engineering: x86, x64, ARM, Windows Kernel, Reversing Tools, and Obfuscation
Bruce Dang - 2014
Reverse engineering is not about reading assembly code, but actually understanding how different pieces/components in a system work. To reverse engineer a system is to understand how it is constructed and how it works. The book provides: Coverage of x86, x64, and ARM. In the past x86 was the most common architecture on the PC; however, times have changed and x64 is becoming the dominant architecture. It brings new complexity and constructs previously not present in x86. ARM ("Advanced RISC Machine) "is very common in embedded / consumer electronic devices; for example, most if not all cell phones run on ARM. All of apple's i-devices run on ARM. This book will be the first book to cover all three.Discussion of Windows kernel-mode code (rootkits/drivers). This topic has a steep learning curve so most practitioners stay away from this area because it is highly complex. However, this book will provide a concise treatment of this topic and explain how to analyze drivers step-by-step.The book uses real world examples from the public domain. The best way to learn is through a combination of concept discussions, examples, and exercises. This book uses real-world trojans / rootkits as examples congruent with real-life scenariosHands-on exercises. End-of-chapter exercises in the form of conceptual questions and hands-on analysis so so readers can solidify their understanding of the concepts and build confidence. The exercises are also meant to teach readers about topics not covered in the book.
Bitcoin for the Befuddled
Conrad Barski - 2014
Already used by people and companies around the world, many forecast that Bitcoin could radically transform the global economy. The value of a bitcoin has soared from less than a dollar in 2011 to well over $1000 in 2013, with many spikes and crashes along the way. The rise in value has brought Bitcoin into the public eye, but the cryptocurrency still confuses many people. Bitcoin for the Befuddled covers everything you need to know about Bitcoin—what it is, how it works, and how to acquire, store, and use bitcoins safely and securely. You'll also learn about Bitcoin's history, its complex cryptography, and its potential impact on trade and commerce. The book includes a humorous, full-color comic explaining Bitcoin concepts, plus a glossary of terms for easy reference.
The Shellcoder's Handbook: Discovering and Exploiting Security Holes
Jack Koziol - 2004
This much-anticipated revision, written by the ultimate group of top security experts in the world, features 40 percent new content on how to find security holes in any operating system or applicationNew material addresses the many new exploitation techniques that have been discovered since the first edition, including attacking "unbreakable" software packages such as McAfee's Entercept, Mac OS X, XP, Office 2003, and VistaAlso features the first-ever published information on exploiting Cisco's IOS, with content that has never before been exploredThe companion Web site features downloadable code files
Learning GNU Emacs
Debra Cameron - 1991
It is also the most powerful and flexible. Unlike all other text editors, GNU Emacs is a complete working environment--you can stay within Emacs all day without leaving. Learning GNU Emacs, 3rd Edition tells readers how to get started with the GNU Emacs editor. It is a thorough guide that will also "grow" with you: as you become more proficient, this book will help you learn how to use Emacs more effectively. It takes you from basic Emacs usage (simple text editing) to moderately complicated customization and programming.The third edition of Learning GNU Emacs describes Emacs 21.3 from the ground up, including new user interface features such as an icon-based toolbar and an interactive interface to Emacs customization. A new chapter details how to install and run Emacs on Mac OS X, Windows, and Linux, including tips for using Emacs effectively on those platforms.Learning GNU Emacs, third edition, covers:How to edit files with EmacsUsing the operating system shell through EmacsHow to use multiple buffers, windows, and framesCustomizing Emacs interactively and through startup filesWriting macros to circumvent repetitious tasksEmacs as a programming environment for Java, C++, and Perl, among othersUsing Emacs as an integrated development environment (IDE)Integrating Emacs with CVS, Subversion and other change control systems for projects with multiple developersWriting HTML, XHTML, and XML with EmacsThe basics of Emacs LispThe book is aimed at new Emacs users, whether or not they are programmers. Also useful for readers switching from other Emacs implementations to GNU Emacs.
Machine Learning for Hackers
Drew Conway - 2012
Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data
Introduction to Machine Learning with Python: A Guide for Data Scientists
Andreas C. Müller - 2015
If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Trevor Hastie - 2001
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.
Python for Data Analysis
Wes McKinney - 2011
It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
Head First Android Development
Jonathan Simon - 2011
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.
Write Great Code: Volume 1: Understanding the Machine
Randall Hyde - 2004
A dirty little secret assembly language programmers rarely admit to, however, is that what you really need to learn is machine organization, not assembly language programming. Write Great Code Vol I, the first in a series from assembly language expert Randall Hyde, dives right into machine organization without the extra overhead of learning assembly language programming at the same time. And since Write Great Code Vol I concentrates on the machine organization, not assembly language, the reader will learn in greater depth those subjects that are language-independent and of concern to a high level language programmer. Write Great Code Vol I will help programmers make wiser choices with respect to programming statements and data types when writing software, no matter which language they use.
Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
Matthew A. Russell - 2011
You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google