Master effective navigation of neural networks, including convolutions and transformers, to tackle computer vision and NLP tasks using PythonKey FeaturesUnderstand the theory, mathematical foundations and structure of deep neural networksBecome familiar with transformers, large language models, and convolutional networksLearn how to apply them to various computer vision and natural language processing problemsPurchase of the print or K...

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision proble...

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python librariesKey FeaturesBuild a strong foundation in neural networks and deep learning with Python librariesExplore advanced deep learning techniques and their applications across computer vision and NLPLearn how a computer can navigate in complex environments with reinforcement learningBook DescriptionWith the surge in artificia...

A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math.Ever since computers began beating us at chess, they've been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare.Deep learning is the source of many of thes...

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis.You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical...

This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesLearn applied machine learning with a solid foundation in theoryClear, intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expan...

Unlock the groundbreaking advances of deep learning with this extensively revised edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world.In Deep Learning with Python, Second Edition you will learn:Deep learning from first principlesImage classification & image segmentationTimeseries forecastingText classification...

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guideKey Features\[\*\] Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide.\[\*\] Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation.\[\*\] Get a solid foundation for your entr...

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.Rather than simp...

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...

Publisher\\'s Note: This edition from 2018 is outdated and not compatible with any of the most recent updates to Python libraries. A new third edition, updated for 2020 with six new chapters that include multi-agent methods, discrete optimization, RL in robotics, and advanced exploration techniques is now available.Key FeaturesExplore deep reinforcement learning (RL), from the first principles to the latest algorithmsEvaluate high-profile RL methods, in...

SummaryDeep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.About the TechnologyMachine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, ...