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Deep Learning from Scratch Building with Python from First Principles

neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural;

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Recurrent Neural Networks with Python Quick Start Guide

Recurrent Neural Network models with practical use-cases. Exposure to Python programming is required. Previous experience with TensorFlow will be;

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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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Reinforcement Learning for Finance

generative adversarial networks with examples using the TensorFlow Python library. It also serves as a quick hands-on guide to TensorFlow programming;

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Hands-on Machine Learning with Python

unsupervised learning Examine convolutional neural networks and Recurrent neural networks Get acquainted with scikit-learn and PyTorch Predict;

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Hands-on Machine Learning with Python

* Examine convolutional neural networks and Recurrent neural networks * Get acquainted with scikit-learn and PyTorch * Predict sequences;

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Recurrent Neural Networks

scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Deep Learning with Python

practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll start with a perspective on how;

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Deep Learning with Python

practical know-how with PyTorch, a platform developed by Facebooks Artificial Intelligence Research Group. You'll start with a perspective on;

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TensorFlow 2.0 Quick Start Guide

techniques such as training neural networks Get acquainted with some new practices introduced in TensorFlow 2.0 Alpha Book DescriptionTensorFlow;

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Neural Network Programming with Python

network works is also explored. You are then guided on how to implement neural networks with Neupy, another Python library.The following topics;

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Advanced Deep Learning with Python

networks using the Python ecosystem Key Features Get to grips with building faster and more robust deep learning architectures Investigate and;

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Python Deep Learning

foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications across;

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Deep Learning with Keras

you are a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this;

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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Convolutional Neural Networks in Visual Computing

guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;

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Convolutional Neural Networks in Visual Computing

guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;

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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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Make Your Own Neural Network

A step-by-step gentle journey through the mathematics of neural networks, and making your own using the Python computer language. Neural;

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Deep Neuro-Fuzzy Systems with Python

world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python. You'll start by walking through;

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Hands-On Deep Learning with TensorFlow

convoluted neural networks, then this book is for you. Some familiarity with C++ or Python is assumed. What You Will Learn * Set up your;

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PyTorch Deep Learning Hands-On

Recurrent Neural Networks - work with sequential data such as natural language and audio Generative Adversarial Networks - create new content with;

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Neural Network Programming with Java

implement these in Java. Recurrent neural networks, which are believed to have memory, are discussed in detail. These work in such a way that the;

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Python Crash Course, 3rd Edition

Since its initial debut in 2015, this critically acclaimed quick-start guide to programming has taught millions of people all over the;

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