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...

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 ...

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...

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...

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...

If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes...

Get to grips with the basics of Keras to implement fast and efficient deep-learning modelsKey FeaturesImplement various deep learning algorithms in Keras and see how deep learning can be used in gamesSee how various deep learning models and practical use-cases can be implemented using KerasA practical, hands-on guide with real-world examples to give you a strong foundation in KerasBook DescriptionThis book starts by introduci...

How do the experts solve difficult problems in software development? In this unique and insightful book, leading computer scientists offer case studies that reveal how they found unusual, carefully designed solutions to high-profile projects. You will be able to look over the shoulder of major coding and design experts to see problems through their eyes.This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things....

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...

Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries.Key FeaturesSecond edition of the bestselling book on Machine LearningA practical approach to key frameworks in data science, machine learning, and deep learningUse the most powerful Python libraries to implement machine learning and deep learningGet to know the best practices to improve and optimize you...

Data collection, processing, analysis, and moreAbout This BookYour entry ticket to the world of data science with the stability and power of JavaExplore, analyse, and visualize your data effectively using easy-to-follow examplesA highly practical course covering a broad set of topics - from the basics of Machine Learning to Deep Learning and Big Data frameworks.Who This Book Is ForThis course is meant for...

Named a Notable Book in the 21st Annual Best of Computing list by the ACM!Robert Sedgewick and Kevin Wayne’s Computer Science: An Interdisciplinary Approach is the ideal modern introduction to computer science with Java programming for both students and professionals. Taking a broad, applications-based approach, Sedgewick and Wayne teach through important examples from science, mathematics, engineering, finance, and commercial computing.The book de...