Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you'll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits,...

Humans learn best from feedback--we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills...

"Covers field-defining learning theories ranging from behaviorism (R is for Reward) to cognitive psychology (S is for Self-Explanation) to social psychology (O is for Observation). The chapters also introduce lesser-known theories ... relevant to practice, such as arousal theory (X is for eXcitement). Together the theories, evidence, and strategies from each chapter can be combined ... to create ... learning plans and the means to know if they succeed"--Page...

A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving...

Cet ouvrage, conçu pour tous ceux qui souhaitent s'initier au deep learning (apprentissage profond), est la traduction de la deuxième partie du best-seller Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow (2e édition). Le deep learning est récent et il évolue vite. Ce livre en présente les principales techniques : les réseaux de neurones profonds, capables de modéliser toutes sortes de données, les réseaux de...

This book ... advocate[s] for the informed observation and description of students without subjecting children to eligibility formulas and labels ... [It is] based on the firmly held conviction that the best educational care takes place when parents and educators form a coalition on behalf of the student, which is why the management techniques in this book are framed both for parents and schools ... [It is the author's] hope [that] this book can inspire...

Join deep learning advocate Mark Ryan, the author of the book "Deep Learning with Structured Data" and the liveProject "End-to-End Deep Learning for Price Prediction," on his tour into training the model in Keras and running experiments.

A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving...