LLVM Essentials. Become familiar with the LLVM infrastructure and start using LLVM libraries to design a compiler

Mayur Pandey, Suyog Sarda, David Farago

LLVM is currently the point of interest for many firms, and has a very active open source community. It provides us with a compiler infrastructure that can be used to write a compiler for a language. It provides us with a set of reusable libraries that can be used to optimize code, and a target-independent code generator to generate code for different backends. It also provides us with a lot of other utility tools that can be easily integrated into compiler projects.This book details how you can use the LLVM compiler infrastructure libraries effectively, and will enable you to design your own custom compiler with LLVM in a snap.We start with the basics, where you’ll get to know all about LLVM. We then cover how you can use LLVM library calls to emit intermediate representation (IR) of simple and complex high-level language paradigms. Moving on, we show you how to implement optimizations at different levels, write an optimization pass, generate code that is independent of a target, and then map the code generated to a backend. The book also walks you through CLANG, IR to IR transformations, advanced IR block transformations, and target machines. By the end of this book, you’ll be able to easily utilize the LLVM libraries in your own projects.

jQuery Mobile Cookbook. Over 80 recipes with examples and practical tips to help you quickly learn and develop cross-platform applications with jQuery Mobile book and

Chetan Jain

jQuery Mobile is an award winning, HTML5/CSS3 based open source cross-platform UI framework. It offers a very cool and highly customizable UX. It is built on the popular jQuery library and uses declarative coding making it easy to use and learn. It is the market leader today considering the numerous browsers and platforms that it supports.jQuery Mobile Cookbook presents over a hundred recipes written in a simple and easy manner. You can quickly learn and start writing code immediately. Advanced topics such as using scripts to manipulate, customize, and extend the framework are also covered. These tips address your common everyday problems. The book is very handy for both beginner and experienced jQuery Mobile developers.You start by developing simple apps using various controls and learn to customize them. Later you explore using advanced aspects like configurations, events, and methods.Develop single and multi-page applications. Use caching to boost performance. Use custom transitions, icon sprites, styles, and themes. Learn advanced features like configurations, events, and methods. Explore future trends by using HTML5 new features and semantics with jQuery Mobile.jQuery Mobile Cookbook is an easy read and is packed with practical tips and screenshots.

Penetration Testing with BackBox. This tutorial will immerse you in the fascinating environment of penetration testing. Thoroughly practical and written for ease of understanding, it will give you the insights and knowledge you need to start using BackBox

Stefan Umit Uygur

Joomla! 3 Beginner's Guide. Build, develop, and manage a fully functioning, professional looking, and feature-rich website with the Joomla! CMS

Eric Tiggeler

Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks

Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu

Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts by highlighting the basic building blocks of the natural language processing domain.The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search.By the end of this book, you will not only have sound knowledge of natural language processing, but also be able to select the best text preprocessing and neural network models to solve a number of NLP issues.

Java Deep Learning Cookbook. Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j

Rahul Raj

Java is one of the most widely used programming languages in the world. With this book, you will see how to perform deep learning using Deeplearning4j (DL4J) – the most popular Java library for training neural networks efficiently.This book starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural networks in distributed systems effectively. In addition to this, you will learn how to import models from Keras and change the configuration in a pre-trained DL4J model. Finally, you will explore benchmarking in DL4J and optimize neural networks for optimal results.By the end of this book, you will have a clear understanding of how you can use DL4J to build robust deep learning applications in Java.

Master Data Science with Python. Combine Python with machine learning principles to discover hidden patterns in raw data

Rohan Chopra, Aaron England, Mohamed Noordeen Alaudeen

Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. You will learn three major techniques in machine learning: unsupervised learning, supervised learning, and reinforcement learning. You will also explore basic classification and regression techniques, such as support vector machines, decision trees, and logistic regression.As you make your way through the book, you will understand the basic functions, data structures, and syntax of the Python language that are used to handle large datasets with ease. You will learn about NumPy and pandas libraries for matrix calculations and data manipulation, discover how to use Matplotlib to create highly customizable visualizations, and apply the boosting algorithm XGBoost to make predictions. In the concluding chapters, you will explore convolutional neural networks (CNNs), deep learning algorithms used to predict what is in an image. You will also understand how to feed human sentences to a neural network, make the model process contextual information, and create human language processing systems to predict the outcome.By the end of this book, you will be able to understand and implement any new data science algorithm and have the confidence to experiment with tools or libraries other than those covered in the book.

Python Web Penetration Testing Cookbook. Over 60 indispensable Python recipes to ensure you always have the right code on hand for web application testing

Benjamin May, Cameron Buchanan, Andrew Mabbitt, Dave Mound, ...