Yuxi (Hayden) Liu rozwija modele uczenia maszynowego w Google. Wcześniej pracował naukowo nad zastosowaniami uczenia maszynowego w takich dziedzinach jak reklama internetowa i cyberbezpieczeństwo. Jest entuzjastą edukacji i autorem wielu książek o uczeniu maszynowym. Pierwsze wydanie tego podręcznika zajmowało wiodącą pozycję w rankingu Amazona w latach 2017 i 2018.
Yuxi (Hayden) Liu - książki
Tytuły autora: Yuxi (Hayden) Liu dostępne w księgarni Helion
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This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.
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PyTorch 1.x Reinforcement Learning Cookbook. Over 60 recipes to design, develop, and deploy self-learning AI models using Python PyTorch 1.x Reinforcement Learning Cookbook. Over 60 recipes to design, develop, and deploy self-learning AI models using Python
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This book explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations to help you understand the concepts and ideas required to build efficient artificial intelligence systems, this book will help you construct deep models using popular frameworks and datasets.
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Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras
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R is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. This book demonstrates end-to-end implementations of five real-world projects on popular topics in deep learning such as handwritten digit recognition, traffic light detection, fraud detection, text generat
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R Deep Learning Projects. Master the techniques to design and develop neural network models in R R Deep Learning Projects. Master the techniques to design and develop neural network models in R
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Data science and machine learning are some of the top buzzwords in the technical world today. A re-surging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. Through this book, you will learn to apply the concepts of mach
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Python Machine Learning By Example. The easiest way to get into machine learning Python Machine Learning By Example. The easiest way to get into machine learning
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