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Neural Networks with TensorFlow and Keras: Training, Generative Models, and Reinforcement Learning by Philip Hua at Abbey's Bookshop,
Neural Networks with TensorFlow and Keras: Training, Generative Models, and Reinforcement Learning
— —
Philip Hua

Neural Networks with TensorFlow and Keras

Training, Generative Models, and Reinforcement Learning

Philip Hua

$111.95   $89.44

Paperback

Not in-store but you can order this
How long will it take?
English
APress
01 January 2025
Programming & scripting languages: general; Machine learning
Explore the capabilities of machine learning and neural networks. This comprehensive guidebook is tailored for professional programmers seeking to deepen their understanding of neural networks, machine learning techniques, and large language models (LLMs).

The book explores the core of machine learning techniques, covering essential topics such as data pre-processing, model selection, and customization. It provides a robust foundation in neural network fundamentals, supplemented by practical case studies and projects. You will explore various network topologies, including Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) networks, Variational Autoencoders (VAE), Generative Adversarial Networks (GAN), and Large Language Models (LLMs). Each concept is explained with clear, step-by-step instructions and accompanied by Python code examples using the latest versions of TensorFlow and Keras, ensuring a hands-on learning experience.

By the end of this book, you will gain practical skills to apply these techniques to solving problems. Whether you are looking to advance your career or enhance your programming capabilities, this book provides the tools and knowledge needed to excel in the rapidly evolving field of machine learning and neural networks.

 

What You Will Learn

Grasp the fundamentals of various neural network topologies, including DNN, RNN, LSTM, VAE, GAN, and LLMs Implement neural networks using the latest versions of TensorFlow and Keras, with detailed Python code examples Know the techniques for data pre-processing, model selection, and customization to optimize machine learning models Apply machine learning and neural network techniques in various professional scenarios

 

Who This Book Is For

Data scientists, machine learning enthusiasts, and software developers who wish to deepen their understanding of neural networks and machine learning techniques
By:  
Imprint:   APress
Country of Publication:   United States
Dimensions:   Height: 235mm,  Width: 155mm, 
ISBN:   9798868810190
Pages:   178
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Chapter 1: Introduction to Neural Networks.- Chapter 2: Using Tensors.- Chapter 3: How Machines Learn.- Chapter 4: Network Layers.- Chapter 5: The Training Process.- Chapter 6: Generative Models.- Chapter 7: Re-enforcement Learning.- Chapter 8: Using Pre-trained Networks.

Philip Hua brings over 30 years of experience in investment, risk management, and IT. He has held senior positions as a partner at a hedge fund, led risk and IT departments at both large and boutique firms, and co-founded a successful fintech company. Alongside Dr. Paul Wilmott, he developed the CrashMetrics methodology, a crucial tool for evaluating severe market risk in portfolios. Philip holds a PhD in Applied Mathematics from Imperial College London, an MBA, and a BSc in Engineering.          

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