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Python Machine Learning
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This Book
  • Leverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualization
  • Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms
  • Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets
Who This Book Is ForIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will Learn
  • Explore how to use different machine learning models to ask different questions of your data
  • Learn how to build neural networks using Keras and Theano
  • Find out how to write clean and elegant Python code that will optimize the strength of your algorithms
  • Discover how to embed your machine learning model in a web application for increased accessibility
  • Predict continuous target outcomes using regression analysis
  • Uncover hidden patterns and structures in data with clustering
  • Organize data using effective pre-processing techniques
  • Get to grips with sentiment analysis to delve deeper into textual and social media data
In DetailMachine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you’ll soon be able to answer some of the most important questions facing you and your organization.Style and approachPython Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Published by: Packt Publishing | Publication date: 09/23/2015
Kindle book details: Kindle Edition, 456 pages

Node.js Web Development - Third Edition
Create real-time server-side applications with this practical, step-by-step guideAbout This Book
  • Learn about server-side JavaScript with Node.js and Node modules through the most up-to-date book on Node.js web development
  • Understand website development both with and without the Connect/Express web application framework
  • Develop both HTTP server and client applications
Who This Book Is ForThis book is for anybody looking for an alternative to the "P" languages (Perl, PHP, and Python), or anyone looking for a new paradigm of server-side application development. You should have at least a rudimentary understanding of JavaScript and web application development.What You Will Learn
  • Install and use Node.js for both development and deployment
  • Use the Express application framework
  • Configure Bootstrap for mobile-first theming
  • Use data storage engines such as MySQL, SQLITE3, and MongoDB
  • Understand user authentication methods, including OAuth, with third-party services
  • Deploy Node.js to live servers, including microservice development with Docker
  • Perform unit testing with Mocha
  • Perform functional testing of the web application with CasperJS
In DetailNode.js is a server-side JavaScript platform using an event driven, non-blocking I/O model allowing users to build fast and scalable data-intensive applications running in real time. Node.js Web Development shows JavaScript is not just for browser-side applications. It can be used for server-side web application development, real-time applications, microservices, and much more.This book gives you an excellent starting point, bringing you straight to the heart of developing web applications with Node.js. You will progress from a rudimentary knowledge of JavaScript and server-side development to being able to create and maintain your own Node.js application. With this book you'll learn how to use the HTTP Server and Client objects, data storage with both SQL and MongoDB databases, real-time applications with Socket.IO, mobile-first theming with Bootstrap, microservice deployment with Docker, authenticating against third-party services using OAuth, and much more.Style and ApproachThis book is a practical guide for anyone looking to develop striking and robust web applications using Node.js.
Author: David Herron
Published by: Packt Publishing | Publication date: 06/27/2016
Kindle book details: Kindle Edition, 376 pages

Learning JavaScript Data Structures and Algorithms - Second Edition
Key Features
  • Understand common data structures and the associated algorithms, as well as the context in which they are used.
  • Master existing JavaScript data structures such as array, set and map and learn how to implement new ones such as stacks, linked lists, trees and graphs.
  • All concepts are explained in an easy way, followed by examples.
Book DescriptionThis book begins by covering basics of the JavaScript language and introducing ECMAScript 7, before gradually moving on to the current implementations of ECMAScript 6. You will gain an in-depth knowledge of how hash tables and set data structure functions, as well as how trees and hash maps can be used to search files in a HD or represent a database. This book is an accessible route deeper into JavaScript. Graphs being one of the most complex data structures you'll encounter, we'll also give you a better understanding of why and how graphs are largely used in GPS navigation systems in social networks.Toward the end of the book, you'll discover how all the theories presented by this book can be applied in real-world solutions while working on your own computer networks and Facebook searches.What you will learn
  • Declare, initialize, add, and remove items from arrays, stacks, and queues
  • Get the knack of using algorithms such as DFS (Depth-first Search) and BFS (Breadth-First Search) for the most complex data structures
  • Harness the power of creating linked lists, doubly linked lists, and circular linked lists
  • Store unique elements with hash tables, dictionaries, and sets
  • Use binary trees and binary search trees
  • Sort data structures using a range of algorithms such as bubble sort, insertion sort, and quick sort
About the AuthorLoiane Groner has over 10 years of experience in developing enterprise applications. She has worked at multinational companies, such as IBM, and nowadays she works as Software Development Manager at a financial institution, where she manages overseas solutions. Her areas of expertise include Java, Sencha technologies (Ext JS), and hybrid mobile development with PhoneGap and Ionic.She is passionate about technology, and she has dedicated herself to spreading knowledge in the software development community through her blog, as guest speaker in IT conferences, and also as guest professor in university extension courses.While at university, she worked as teacher's assistant for 2 years for the Algorithms, Data Structures, and Computing Theory classes. She represented her university at the ACM International Collegiate Programming Contest – Brazilian Finals (South America Regionals) and also worked as Student Delegate of SBC (Brazilian Computing Society). She won a merit award in her Senior year for being one of top three students with better GPAs in the Computer Science department and has also graduated with honors.Loiane is also the author of the books Ext JS 4 First Look, Mastering Ext JS, Mastering Ext JS - Second Edition, Sencha Architect App Development, Learning JavaScript Data Structures and Algorithms, and JavaScript Regular Expression, all of them published by Packt Publishing.If you want to keep in touch, you can find Loiane on Facebook (, Twitter (@loiane), and also on Github ( of Contents
  • JavaScript—A Quick Overview
  • Arrays
  • Stacks
  • Queues
  • Linked Lists
  • Sets
  • Dictionaries and Hashes
  • Trees
  • Graphs
  • Sorting and Searching Algorithms
  • Patterns of Algorithm
  • Algorithm Complexity
  • Published by: Packt Publishing | Publication date: 06/23/2016
    Kindle book details: Kindle Edition, 314 pages

    Machine Learning with R - Second Edition - Deliver Data Insights with R and Predictive Analytics
    Key Features
    • Harness the power of R for statistical computing and data science
    • Explore, forecast, and classify data with R
    • Use R to apply common machine learning algorithms to real-world scenarios
    Book DescriptionMachine learning, at its core, is concerned with transforming data into actionable knowledge. This makes machine learning well suited to the present-day era of big data. Given the growing prominence of Râa cross-platform, zero-cost statistical programming environmentâthere has never been a better time to start applying machine learning to your data. Whether you are new to data analytics or a veteran, machine learning with R offers a powerful set of methods to quickly and easily gain insights from your data.Want to turn your data into actionable knowledge, predict outcomes that make real impact, and have constantly developing insights? R gives you access to the cutting-edge power you need to master exceptional machine learning techniques.Updated and upgraded to the latest libraries and most modern thinking, the second edition of Machine Learning with R provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience.With this book youâll discover all the analytical tools you need to gain insights from complex data and learn how to to choose the correct algorithm for your specific needs. Through full engagement with the sort of real-world problems data-wranglers face, youâll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering. Transform the way you think about data; discover machine learning with R.What you will learn
    • Harness the power of R to build common machine learning algorithms with real-world data science applications
    • Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results
    • Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems
    • Classify your data with Bayesian and nearest neighbour methods
    • Predict values by using R to build decision trees, rules, and support vector machines
    • Forecast numeric values with linear regression, and model your data with neural networks
    • Evaluate and improve the performance of machine learning models
    • Learn specialized machine learning techniques for text mining, social network data, big data, and more
    About the AuthorBrett Lantz has used innovative data methods to understand human behavior for more than 10 years. A sociologist by training, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles. Since then, he has worked on the interdisciplinary studies of cellular telephone calls, medical billing data, and philanthropic activity, among others.Table of Contents
  • Introducing Machine Learning
  • Managing and Understanding Data
  • Lazy Learning â Classification Using Nearest Neighbors
  • Probabilistic Learning â Classification Using Naive Bayes
  • Divide and Conquer â Classification Using Decision Trees and Rules
  • Forecasting Numeric Data â Regression Methods
  • Black Box Methods â Neural Networks and Support Vector Machines
  • Finding Patterns â Market Basket Analysis Using Association Rules
  • Finding Groups of Data â Clustering with K-means
  • Evaluating Model Performance
  • Improving Model Performance
  • Specialized Machine Learning Topics
  • Author: Brett Lantz
    Published by: Packt Publishing | Publication date: 07/31/2015
    Kindle book details: Kindle Edition, 454 pages

    Nmap: Network Exploration and Security Auditing Cookbook - Second Edition
    Key Features
    • Get the first book on the market that unleashes the new Nmap 7 and ensures effective network security
    • Master the skills of Nmap Scripting Engine and deep dive into new auditing techniques
    • Work through practical recipes to get to grips with the powerful features of Nmap 7
    Book DescriptionThis update to Nmap 6: Network Exploration and Security Auditing Cookbook brings you the latest enhancements and features of Nmap 7. Using practical recipes, we’ll help you get to grips with the latest changes in Nmap Scripting Engine and other functionalities.To start, you’ll learn about the new scripts and libraries that Nmap 7 has to offer, which support various platform and operating systems. We’ll show you how to scan faster and generate reports with the performance boost in Nmap 7. You will also be able to scan Windows machines and ICS/SCADA systems to detect common misconfigurations and vulnerabilities, and to obtain information. Finally, you will be able to create your own Nmap Scripting Engine scripts to expand the capabilities of Nmap. It also shows you how to leverage the enhanced functionalities of Nmap 7.What you will learn
    • See how to use Nmap, Ncat, Ncrack, Ndiff, NSE, and Zenmap
    • Master basic and advanced techniques to perform port scanning and host discovery
    • Detect insecure configurations and vulnerabilities in web servers, databases, and mail servers
    • Scan Microsoft Windows machines and obtain information from ICS/SCADA systems
    • Gain tips and tricks to perform Internet-wide scans
    • Create reports from the scan results
    • Write your own Nmap Scripting Engine scripts
    About the AuthorPaulino Calderon Pale (@calderpwn) is a passionate information security consultant living in a Caribbean island in Mexico called Cozumel. Paulino learned programming and network security early in his life, and these skills came in handy when he joined the information security industry 6 years ago.He is the co-founder of Websec, a company based in Canada and Mexico offering pentesting, source code auditing, and vulnerability assessment services. Today, some of his software is used by millions around the world and has become a regular contributor to the open source community. He still loves learning new technologies and conducting big data research. He also loves attending IT events and has given talks and held workshops in Canada, the United States, Mexico, and South America.In the summer of 2011, Paulino joined the Nmap development team as part of Google's Summer of Code program to work as a NSE developer. He focused on improving the web scanning capabilities of Nmap and has kept on contributing to the project since then. In 2015, he was part of Google’s Summer of Code program again, but this time mentoring a student dedicated to vulnerability detection and exploitation.
    Published by: Packt Publishing | Publication date: 05/26/2017
    Kindle book details: Kindle Edition, 416 pages

    Machine Learning with R
    In DetailMachine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data."Machine Learning with R" is a practical tutorial that uses hands-on examples to step through real-world application of machine learning. Without shying away from the technical details, we will explore Machine Learning with R using clear and practical examples. Well-suited to machine learning beginners or those with experience. Explore R to find the answer to all of your questions.How can we use machine learning to transform data into action? Using practical examples, we will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process.We will learn how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data."Machine Learning with R" will provide you with the analytical tools you need to quickly gain insight from complex data.ApproachWritten as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Who this book is forIntended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.
    Author: Brett Lantz
    Published by: Packt Publishing | Publication date: 10/25/2013
    Kindle book details: Kindle Edition, 398 pages Enterprise Architecture
    Blend industry best practices to architect and deliver packaged applications that cater to enterprise business needsAbout This Book
    • Build your own application from start to finish, making use of unique tools and platform features
    • Learn how to use the platform to build a truly integrated, scalable, and robustly engineered application to design, develop, package, and support an application focusing on enterprise-level customer demands
    • Build the first iteration of your own ready-to-install packaged application with the help of a mix of step-by-step, worked examples and tips and tricks that discuss and answer key architectural questions
    Who This Book Is ForThis book is for advanced developers and architects who need to understand the Salesforce platform from the perspective of enterprise-level requirements. You should have an existing understanding of Apex and Visualforce. Those familiar with other enterprise software ecosystems will also find this book ideal as they adopt You Will Learn
    • Learn how to package, install, test, and upgrade an application, and understand how best to license and support an application
    • Define architecture-aligning data storage and functional requirements with the platform for a consistent and integrated user experience using the platform’s declarative features
    • Develop Apex code that is easy to navigate, self-documenting, testable, robust, and organic leveraging the Separation of Concerns principle
    • Leverage your application's client-agnostic Service layer backbone to support numerous platform areas such as Batch, Scheduler, Visualforce, and the latest Salesforce1 client
    • Apply querying, indexing and asynchronous best practices, guidelines, and patterns for large data volumes and complex processes covering custom indexes and Batch Apex
    • Explore approaches and tips on how to develop advanced application life cycle processes around Source Control, Continuous Integration, and testing, utilizing the Metadata and Tooling APIs from Salesforce
    In DetailSuccessful enterprise applications require planning, commitment, and investment in understanding the best practices, processes, tools, and features available.This book will teach you how to architect and support enduring applications for enterprise clients with Salesforce by exploring how to identify architecture needs and design solutions based on industry standard patterns. As your development team grows, managing the development cycle with more robust application life cycle tools and using approaches such as Continuous Integration becomes increasingly important. There are many ways to build solutions on—this book cuts a logical path through the steps and considerations for building packaged solutions from start to finish, covering all aspects from engineering to getting your application into the hands of your customers, and ensuring that they get the best value possible from your application.
    Published by: Packt Publishing | Publication date: 09/25/2014
    Kindle book details: Kindle Edition, 402 pages

    Python Data Structures and Algorithms
    Key Features
    • A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures.
    • Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures.
    • Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner.
    Book DescriptionData structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications.What you will learn
    • Gain a solid understanding of Python data structures.
    • Build sophisticated data applications.
    • Understand the common programming patterns and algorithms used in Python data science.
    • Write efficient robust code.
    About the AuthorBenjamin Baka works as a software developer and has over 10 years, experience in programming. He is a graduate of Kwame Nkrumah University of Science and Technology and a member of the Linux Accra User Group. Notable in his language toolset are C, C++, Java, Python, and Ruby. He has a huge interest in algorithms and finds them a good intellectual exercise.He is a technology strategist and software engineer at mPedigree Network, weaving together a dizzying array of technologies in combating counterfeiting activities, empowering consumers in Ghana, Nigeria, and Kenya to name a few.In his spare time, he enjoys playing the bass guitar and listening to silence. You can find him on his blog.Table of Contents
  • Python objects, types and expressions
  • Python data types and structures
  • Principles of data structure design
  • Lists and pointer structures
  • Stacks and Queues
  • Trees
  • Hashing and symbol tables
  • Graphs and other algorithms
  • Searching
  • Sorting
  • Selction Algorithms
  • Design Ttechniques and Sstrategies
  • Implementations, applications and tools
  • Published by: Packt Publishing | Publication date: 05/30/2017
    Kindle book details: Kindle Edition, 310 pages

    Learning Docker - Second Edition
    Docker lets you create, deploy, and manage your applications anywhere at anytime – flexibility is key so you can deploy stable, secure, and scalable app containers across a wide variety of platforms and delve into microservices architectureAbout This Book
    • This up-to-date edition shows how to leverage Docker's features to deploy your existing applications
    • Learn how to package your applications with Docker and build, ship, and scale your containers
    • Explore real-world examples of securing and managing Docker containers
    Who This Book Is ForThis book is ideal for developers, operations managers, and IT professionals who would like to learn about Docker and use it to build and deploy container-based apps. No prior knowledge of Docker is expected.What You Will Learn
    • Develop containerized applications using the Docker version 17.03
    • Build Docker images from containers and launch them
    • Develop Docker images and containers leveraging Dockerfiles
    • Use Docker volumes to share data
    • Get to know how data is shared between containers
    • Understand Docker Jenkins integration
    • Gain the power of container orchestration
    • Familiarize yourself with the frequently used commands such as docker exec, docker ps, docker top, and docker stats
    In DetailDocker is an open source containerization engine that offers a simple and faster way for developing and running software. Docker containers wrap software in a complete filesystem that contains everything it needs to run, enabling any application to be run anywhere – this flexibily and portabily means that you can run apps in the cloud, on virtual machines, or on dedicated servers.This book will give you a tour of the new features of Docker and help you get started with Docker by building and deploying a simple application. It will walk you through the commands required to manage Docker images and containers. You'll be shown how to download new images, run containers, list the containers running on the Docker host, and kill them.You'll learn how to leverage Docker's volumes feature to share data between the Docker host and its containers – this data management feature is also useful for persistent data. This book also covers how to orchestrate containers using Docker compose, debug containers, and secure containers using the AppArmor and SELinux security modules.Style and approachThis step-by-step guide will walk you through the features and use of Docker, from Docker software installation to the impenetrable security of containers.
    Published by: Packt Publishing | Publication date: 05/31/2017
    Kindle book details: Kindle Edition, 300 pages

    Mastering Embedded Linux Programming - Second Edition
    Key Features
    • Discover how to build and configure reliable embedded Linux devices
    • This book has been updated to include Linux 4.9 and Yocto Project 2.2 (Morty)
    • This comprehensive guide covers the remote update of devices in the field and power management
    Book DescriptionEmbedded Linux runs many of the devices we use every day, from smart TVs to WiFi routers, test equipment to industrial controllers - all of them have Linux at their heart. Linux is a core technology in the implementation of the inter-connected world of the Internet of Things.The comprehensive guide shows you the technologies and techniques required to build Linux into embedded systems. You will begin by learning about the fundamental elements that underpin all embedded Linux projects: the toolchain, the bootloader, the kernel, and the root filesystem. You'll see how to create each of these elements from scratch, and how to automate the process using Buildroot and the Yocto Project.Moving on, you'll find out how to implement an effective storage strategy for flash memory chips, and how to install updates to the device remotely once it is deployed. You'll also get to know the key aspects of writing code for embedded Linux, such as how to access hardware from applications, the implications of writing multi-threaded code, and techniques to manage memory in an efficient way. The final chapters show you how to debug your code, both in applications and in the Linux kernel, and how to profile the system so that you can look out for performance bottlenecks.By the end of the book, you will have a complete overview of the steps required to create a successful embedded Linux system.What you will learn
    • Evaluate the Board Support Packages offered by most manufacturers of a system on chip or embedded module
    • Use Buildroot and the Yocto Project to create embedded Linux systems quickly and efficiently
    • Update IoT devices in the field without compromising security
    • Reduce the power budget of devices to make batteries last longer
    • Interact with the hardware without having to write kernel device drivers
    • Debug devices remotely using GDB, and see how to measure the performance of the systems using powerful tools such as perk, ftrace, and valgrind
    • Find out how to configure Linux as a real-time operating system
    About the AuthorChris Simmonds is a software consultant and trainer living in southern England. He has almost two decades of experience in designing and building open-source embedded systems. He is the founder and chief consultant at 2net Ltd, which provides professional training and mentoring services in embedded Linux, Linux device drivers, and Android platform development. He has trained engineers at many of the biggest companies in the embedded world, including ARM, Qualcomm, Intel, Ericsson, and General Dynamics. He is a frequent presenter at open source and embedded conferences, including the Embedded Linux Conference and Embedded World. You can see some of his work on the Inner Penguin blog.Table of Contents
  • Starting out
  • Learning about Toolchains
  • All about Bootloaders
  • Porting and Configuring the Kernel
  • Building a Root filesystem
  • Selecting a Build System
  • Creating a storage strategy
  • Updating software in the field
  • Interfacing with Device Drivers
  • Starting up: the init program
  • Power management
  • Learning about processes and threads
  • Managing Memory
  • Debugging with GDB
  • Profiling and tracing
  • Real time programming
  • Published by: Packt Publishing | Publication date: 06/30/2017
    Kindle book details: Kindle Edition, 478 pages
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