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Deep Learning

comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the;

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Practical MATLAB Deep Learning

provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you'll see how these toolboxes provide the;

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Practical MATLAB Deep Learning

provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, yoĆ¼ll see how these toolboxes provide the;

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Artificial Intelligence, Machine Learning, and Deep Learning

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will;

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Deep Learning with Python

FEATURES * Practical code examples * In-depth introduction to Keras * Teaches the difference between Deep Learning and AI ABOUT THE;

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Foundations of Deep Reinforcement Learning

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL;

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Deep Learning for the Life Sciences

genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use;

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Introduction to Deep Learning Business Applications for Developers

personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers;

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Deep Learning for Data Analytics

, performance evaluation, Deep Learning optimization, deep auto-encoders, and deep neural networksProvides readers with an introduction to Deep;

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Introduction to Machine Learning with Applications in Information Security

Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a;

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An Introduction to Variational Autoencoders

In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled;

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Beginning Deep Learning with TensorFlow

of online learners. You'll start with an introduction to AI, where you'll learn the history of neural networks and what sets deep learning apart;

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Introduction to Machine Learning

optimization. End-of-chapter exercises help readers to apply concepts learned. Introduction to Machine Learning can be used in courses for advanced;

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Deep Learning and Linguistic Representation

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range;

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Deep Learning and Linguistic Representation

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range;

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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering;

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Deep Learning Illustrated

Deep learning is one of today's hottest fields. This approach to machine learning is achieving breakthrough results in some of today's;

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Deep Reinforcement Learning Hands-On

edition of the bestselling introduction to deep reinforcement learning, expanded with six new chapters Learn advanced exploration techniques;

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Deep Learning with PyTorch Quick Start Guide

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases;

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Deep Learning from the Basics: Python and Deep Learning

that are otherwise invisible to us. Deep Learning from the Basics begins with a fast-paced introduction to deep learning with Python, its;

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Java Deep Learning Essentials

expand your skillset. Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with;

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Beginning Anomaly Detection Using Python-Based Deep Learning

statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;

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Deep Learning for NLP and Speech Recognition

to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has;

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Deep Learning for Nlp and Speech Recognition

to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has;

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Domain Adaptation in Computer Vision with Deep Learning

This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the;

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Deep Learning

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used;

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An Introduction to Machine Learning

This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches;

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Einde inhoud

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