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Machine Learning with TensorFlow
Machine Learning with TensorFlow

TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine. Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to the money chapters: exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own. ...
PySpark Recipes
PySpark Recipes

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model. Understand the advanced features of PySpark2 and SparkSQL; Optimize your code; Program SparkSQL with Python; Use Spark Streaming and Spark MLlib with Python; Perform graph analysis with GraphFrames. ...
60 Recipes for Apache CloudStack
60 Recipes for Apache CloudStack

Planning to deploy and maintain a public, private, or hybrid cloud service? This cookbook's handy how-to recipes help you quickly learn and install Apache CloudStack, along with several API clients, API wrappers, data architectures, and configuration management technologies that work as part of CloudStack's ecosystem. You'll learn how to use Vagrant, Ansible, Chef, Fluentd, Libcloud, and several other open source tools that let you build and operate CloudStack better and faster. If you're an experienced programmer, system administrator, or DevOps practitioner familiar with bash, Git, package management, and some Python, you're ready to go. ...
Head First Learn to Code
Head First Learn to Code

It's no secret the world around you is becoming more connected, more configurable, more programmable, more computational. You can remain a passive participant, or you can learn to code. With Head First Learn to Code you'll learn how to think computationally and how to write code to make your computer, mobile device, or anything with a CPU do things for you. Using the Python programming language, you'll learn step by step the core concepts of programming as well as many fundamental topics from computer science, such as data structures, storage, abstraction, recursion, and modularity. Based on the latest research in cognitive science and learning theory, Head First Learn to Code 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. ...
Mastering Linux Shell Scripting, 2nd Edition
Mastering Linux Shell Scripting, 2nd Edition

In this book, you'll discover everything you need to know to master shell scripting and make informed choices about the elements you employ. Grab your favorite editor and start writing your best Bash scripts step by step. Get to grips with the fundamentals of creating and running a script in normal mode, and in debug mode. Learn about various conditional statements code snippets, and realize the power of repetition and loops in your shell script. You will also learn to write complex shell scripts. This book will also deep dive into file system administration, directories, and system administration like networking, process management, user authentications, and package installation and regular expressions. Towards the end of the book, you will learn how to use Python as a BASH Scripting alternative. By the end of this book, you will know shell scripts at the snap of your fingers and will be able to automate and communicate with your system with keyboard expressions. Make, execut ...
Network Security Through Data Analysis, 2nd Edition
Network Security Through Data Analysis, 2nd Edition

Traditional intrusion detection and logfile analysis are no longer enough to protect today's complex networks. In the updated second edition of this practical guide, security researcher Michael Collins shows InfoSec personnel the latest techniques and tools for collecting and analyzing network traffic datasets. You'll understand how your network is used, and what actions are necessary to harden and defend the systems within it. In three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. New chapters focus on active monitoring and traffic manipulation, insider threat detection, data mining, regression and machine learning, and other topics. Use sensors to collect network, service, host, and active domain data; Work with the SiLK toolset, Python, and other tools and techniques for manipulating data you collect; Detect unusual phenomena through exploratory data analysis (EDA ...
Fundamentals of Deep Learning
Fundamentals of Deep Learning

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that's paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you're familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks; Learn how to train feed-forward neural networks; Use TensorFlow to implement your first neural network; Manage problems that arise as you begin to make networks deeper; Build neural networks that analyze complex images; Perform effective dimensionali ...
CoffeeScript in Action
CoffeeScript in Action

JavaScript runs (almost) everywhere but it can be quirky and awkward. Its cousin CoffeeScript is easier to comprehend and compose. An expressive language, not unlike Ruby or Python, it compiles into standard JavaScript without modification and is a great choice for complex web applications. It runs in any JavaScript-enabled environment and is easy to use with Node.js and Rails. CoffeeScript in Action teaches you how, where, and why to use CoffeeScript. It immerses you in CoffeeScript's comfortable syntax before diving into the concepts and techniques you need in order to write elegant CoffeeScript programs. Throughout, you'll explore programming challenges that illustrate CoffeeScript's unique advantages. For language junkies, the book explains how CoffeeScript brings idioms from other languages into JavaScript. ...
Google Compute Engine
Google Compute Engine

Learn how to run large-scale, data-intensive workloads with Compute Engine, Google's cloud platform. Written by Google engineers, this tutorial walks you through the details of this Infrastructure as a Service by showing you how to develop a project with it from beginning to end. You'll learn best practices for using Compute Engine, with a focus on solving practical problems. With programming examples written in Python and JavaScript, you'll also learn how to use Compute Engine with Docker containers and other platforms, frameworks, tools, and services. Discover how this IaaS helps you gain unparalleled performance and scalability with Google's advanced storage and computing technologies. ...
Linked Data
Linked Data

The current Web is mostly a collection of linked documents useful for human consumption. The evolving Web includes data collections that may be identified and linked so that they can be consumed by automated processes. The W3C approach to this is Linked Data and it is already used by Google, Facebook, IBM, Oracle, and government agencies worldwide. Linked Data presents practical techniques for using Linked Data on the Web via familiar tools like JavaScript and Python. You'll work step-by-step through examples of increasing complexity as you explore foundational concepts such as HTTP URIs, the Resource Description Framework (RDF), and the SPARQL query language. Then you'll use various Linked Data document formats to create powerful Web applications and mashups. ...
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