Mastering TensorFlow 2.x is a must to read and practice if you are interested in building various kinds of neural networks with high level TensorFlow and Keras APIs. The book begins with the basics of TensorFlow and neural network concepts, and goes into specific topics like image classification, object detection, time series forecasting and Generative Adversarial Networks.While we are practicing TensorFlow 2.6 in this book, the version of Tensorflow will change with time, however you can ...

Create scalable machine learning applications to power a modern data-driven business using Spark 2.xKey Features\[\*\] Get to the grips with the latest version of Apache Spark\[\*\] Utilize Spark's machine learning library to implement predictive analytics\[\*\] Leverage Spark’s powerful tools to load, analyze, clean, and transform your dataBook DescriptionThis book will teach you about popular machine learning algorithms and...

Leverage the power of deep learning and Keras to develop smarter and more efficient data modelsKey FeaturesUnderstand different neural networks and their implementation using KerasExplore recipes for training and fine-tuning your neural network modelsPut your deep learning knowledge to practice with real-world use-cases, tips, and tricksBook DescriptionKeras has quickly emerged as a popular deep learning library. Written in P...

Neural Networks and their implementation decoded with TensorFlowKey FeaturesDevelop a strong background in neural network programming from scratch, using the popular Tensorflow library.Use Tensorflow to implement different kinds of neural networks – from simple feedforward neural networks to multilayered perceptrons, CNNs, RNNs and more.A highly practical guide including real-world datasets and use-cases to simplify your understanding of neural...

Strategically design, troubleshoot, and automate Docker containers from development to deploymentKey Features? Docker programming and installation of ecosystem tools and services, Microservices and N-tier applications ? Creating re-usable, portable containers with help of automation tools ? Learning about using Docker in production projects ? Functions of network and inter-link containers ? Attaching volumes securely to containers ? Consuming and troubleshooting...

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach...

Learn to solve challenging data science problems by building powerful machine learning models using PythonAbout This BookUnderstand which algorithms to use in a given context with the help of this exciting recipe-based guideThis practical tutorial tackles real-world computing problems through a rigorous and effective approachBuild state-of-the-art models and develop personalized recommendations to perform machine learning at scal...

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youâ??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includ...

As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA Application Design and Development starts with an introduction to parallel computing concepts for readers with no previous parallel experience, and focuses on issues of immediate importance to working software developers: achiev...

Leverage benefits of machine learning techniques using PythonAbout This BookImprove and optimise machine learning systems using effective strategies.Develop a strategy to deal with a large amount of data.Use of Python code for implementing a range of machine learning algorithms and techniques.Who This Book Is ForThis title is for data scientist and researchers who are already into the field of data scienc...

The leading introduction to computer algorithms in use today, including fifty algorithms every programmer should knowPrinceton Computer Science professors, Robert Sedgewick and Kevin Wayne, survey the most important computer algorithms in use and of interest to anyone working in science, mathematics, and engineering, and those who use computation in the liberal arts. They provide a full treatment of data structures and algorithms for key areas that enable you to co...

OpenStack was created with the audacious goal of being the ubiquitous software choice for building public and private cloud infrastructures. In just over a year, it's become the most talked-about project in open source. This concise book introduces OpenStack's general design and primary software components in detail, and shows you how to start using it to build cloud infrastructures.If you're a developer, technologist, or system administrator familiar with cloud offerings such as R...