Generative Adversarial Networks Projects. Build next-generation generative models using TensorFlow and Keras

Kailash Ahirwar

Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain.Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation.By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects.

Java EE 8 Cookbook. Build reliable applications with the most robust and mature technology for enterprise development

Elder Moraes

Java EE is a collection of technologies and APIs to support Enterprise Application development. The choice of what to use and when can be dauntingly complex for any developer. This book will help you master this. Packed with easy to follow recipes, this is your guide to becoming productive with Java EE 8.You will begin by seeing the latest features of Java EE 8, including major Java EE 8 APIs and specifications such as JSF 2.3, and CDI 2.0, and what they mean for you.You will use the new features of Java EE 8 to implement web-based services for your client applications. You will then learn to process the Model and Streaming APIs using JSON-P and JSON-B and will learn to use the Java Lambdas support offered in JSON-P. There are more recipes to fine-tune your RESTful development, and you will learn about the Reactive enhancements offered by the JAX-RS 2.1 specification.Later on, you will learn about the role of multithreading in your enterprise applications and how to integrate them for transaction handling. This is followed by implementing microservices with Java EE and the advancements made by Java EE for cloud computing.The final set of recipes shows you how take advantage of the latest security features and authenticate your enterprise application.At the end of the book, the Appendix shows you how knowledge sharing can change your career and your life.

R Data Visualization Recipes. A cookbook with 65+ data visualization recipes for smarter decision-making

Vitor Bianchi Lanzetta

R is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions.This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using ShinyBy the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision.

Practical Data Science Cookbook. Data pre-processing, analysis and visualization using R and Python - Second Edition

Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, ...

As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.

Expert Data Visualization. Advanced information visualization with D3.js 4.x

Jos Dirksen

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecmascript 6 and Typescript

Learning pandas. High performance data manipulation and analysis using Python - Second Edition

Michael Heydt

You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.

Hands-on Machine Learning with JavaScript. Solve complex computational web problems using machine learning

Burak Kanber

In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications.Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data.By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier, and many more to design smarter applications.

Effective Business Intelligence with QuickSight. Boost your business IQ with Amazon QuickSight

Rajesh Nadipalli

Amazon QuickSight is the next-generation Business Intelligence (BI) cloud service that can help you build interactive visualizations on top of various data sources hosted on Amazon Cloud Infrastructure. QuickSight delivers responsive insights into big data and enables organizations to quickly democratize data visualizations and scale to hundreds of users at a fraction of the cost when compared to traditional BI tools.This book begins with an introduction to Amazon QuickSight, feature differentiators from traditional BI tools, and how it fits in the overall AWS big data ecosystem. With practical examples, you will find tips and techniques to load your data to AWS, prepare it, and finally visualize it using QuickSight. You will learn how to build interactive charts, reports, dashboards, and stories using QuickSight and share with others using just your browser and mobile app.The book also provides a blueprint to build a real-life big data project on top of AWS Data Lake Solution and demonstrates how to build a modern data lake on the cloud with governance, data catalog, and analysis. It reviews the current product shortcomings, features in the roadmap, and how to provide feedback to AWS.Grow your profits, improve your products, and beat your competitors.