Hands-On Automation Testing with Java for Beginners. Build automation testing frameworks from scratch with Java

Rahul Shetty

Java is one of the most commonly-used software languages by programmers and developers. Are you from a non-technical background and looking to master Java for your automation needs? Then Hands-On Automation Testing with Java for Beginners is for you.This book provides you with efficient techniques to effectively handle Java-related automation projects. You will learn how to handle strings and their functions in Java. As you make your way through the book, you will get to grips with classes and objects, along with their uses. In the concluding chapters, you will learn about the importance of inheritance and exceptions with practical examples. By the end of this book, you will have gained comprehensive knowledge of Java.

Mastering Spark for Data Science. Lightning fast and scalable data science solutions

Andrew Morgan, Antoine Amend, Matthew Hallett, David George

Data science seeks to transform the world using data, and this is typically achievedthrough disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs.This book deep dives into using Spark to deliver production-grade data sciencesolutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more.You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.

Angular Router. From Angular core team member and creator of the router

Victor Savkin

Managing state transitions is one of the hardest parts of building applications. This is especially true on the web, where you also need to ensure that the state is reflected in the URL. In addition, you might want to split applications into multiple bundles and load them on demand. Doing this transparently isn’t easy. The Angular router solves these problems. Using the router, you can declaratively specify application states, manage state transitions while taking care of the URL, and load bundles on demand.This book is a complete description of the Angular router written by its designer. It goes far beyond a how-to-get-started guide and talks about the library in depth. The mental model, design constraints, and the subtleties of the API-everything is covered. You’ll learn in detail how to use the router in your own applications. Predominantly, you’ll understand the inner workings of the router and how you can configure it to work with any edge cases you come across in your sites.Throughout the book, you’ll see examples from real-world use in the MailApp application. You can view the full source of this application and see how the router code works to manage the state of the application and define what is visible on screen. Reading this book will give you deep insights into why the router works the way it does and will make you an Angular router expert.

Keras Deep Learning Cookbook. Over 30 recipes for implementing deep neural networks in Python

Rajdeep Dua, Manpreet Singh Ghotra

Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning

scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition

Julian Avila, Trent Hauck

Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively.The second edition begins with taking you through recipes on evaluating the statistical properties of data and generates synthetic data for machine learning modelling. As you progress through the chapters, you will comes across recipes that will teach you to implement techniques like data pre-processing, linear regression, logistic regression, K-NN, Naïve Bayes, classification, decision trees, Ensembles and much more. Furthermore, you’ll learn to optimize your models with multi-class classification, cross validation, model evaluation and dive deeper in to implementing deep learning with scikit-learn. Along with covering the enhanced features on model section, API and new features like classifiers, regressors and estimators the book also contains recipes on evaluating and fine-tuning the performance of your model. By the end of this book, you will have explored plethora of features offered by scikit-learn for Python to solve any machine learning problem you come across.

Voice User Interface Projects. Build voice-enabled applications using Dialogflow for Google Home and Alexa Skills Kit for Amazon Echo

Henry Lee

From touchscreen and mouse-click, we are moving to voice- and conversation-based user interfaces. By adopting Voice User Interfaces (VUIs), you can create a more compelling and engaging experience for your users. Voice User Interface Projects teaches you how to develop voice-enabled applications for desktop, mobile, and Internet of Things (IoT) devices.This book explains in detail VUI and its importance, basic design principles of VUI, fundamentals of conversation, and the different voice-enabled applications available in the market. You will learn how to build your first voice-enabled application by utilizing DialogFlow and Alexa’s natural language processing (NLP) platform. Once you are comfortable with building voice-enabled applications, you will understand how to dynamically process and respond to the questions by using NodeJS server deployed to the cloud. You will then move on to securing NodeJS RESTful API for DialogFlow and Alexa webhooks, creating unit tests and building voice-enabled podcasts for cars. Last but not the least you will discover advanced topics such as handling sessions, creating custom intents, and extending built-in intents in order to build conversational VUIs that will help engage the users.By the end of the book, you will have grasped a thorough knowledge of how to design and develop interactive VUIs.

Natural Language Processing with TensorFlow. Teach language to machines using Python's deep learning library

Thushan Ganegedara

Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks.Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator.After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks.

Kali Linux Network Scanning Cookbook. A Step-by-Step Guide leveraging Custom Scripts and Integrated Tools in Kali Linux - Second Edition

Michael Hixon, Justin Hutchens

With the ever-increasing amount of data flowing in today’s world, information security has become vital to any application. This is where Kali Linux comes in. Kali Linux focuses mainly on security auditing and penetration testing. This step-by-step cookbook on network scanning trains you in important scanning concepts based on version 2016.2. It will enable you to conquer any network environment through a range of network scanning techniques and will also equip you to script your very own tools.Starting with the fundamentals of installing and managing Kali Linux, this book will help you map your target with a wide range of network scanning tasks, including discovery, port scanning, fingerprinting, and more. You will learn how to utilize the arsenal of tools available in Kali Linux to conquer any network environment. The book offers expanded coverage of the popular Burp Suite and has new and updated scripts for automating scanning and target exploitation. You will also be shown how to identify remote services, how to assess security risks, and how various attacks are performed. You will cover the latest features of Kali Linux 2016.2, which includes the enhanced Sparta tool and many other exciting updates.This immersive guide will also encourage the creation of personally scripted tools and the skills required to create them.