Neural Networks with Tensorflow and Keras: Training, Generative Models, and Reinforcement Learning
暫譯: 使用 Tensorflow 和 Keras 的神經網絡：訓練、生成模型與強化學習

Hua, Philip

Neural Networks with Tensorflow and Keras: Training, Generative Models, and Reinforcement Learning
  • 出版商: Apress
  • 出版日期: 2025-01-22
  • 售價: $1,730
  • 貴賓價: 9.5 折 $1,644
  • 語言: 英文
  • 頁數: 270
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868810190
  • ISBN-13: 9798868810190
  • 相關分類: DeepLearning、Reinforcement、TensorFlow

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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

商品描述(中文翻譯)

探索機器學習和神經網絡的能力。本書是為專業程式設計師量身打造，旨在加深他們對神經網絡、機器學習技術和大型語言模型（LLMs）的理解。

本書探討機器學習技術的核心，涵蓋數據預處理、模型選擇和自定義等基本主題。它提供了神經網絡基礎的堅實基礎，並輔以實用的案例研究和專案。您將探索各種網絡拓撲，包括深度神經網絡（DNN）、循環神經網絡（RNN）、長短期記憶（LSTM）網絡、變分自編碼器（VAE）、生成對抗網絡（GAN）和大型語言模型（LLMs）。每個概念都以清晰的逐步指導進行解釋，並附有使用最新版本的TensorFlow和Keras的Python代碼示例，確保實踐學習的體驗。

在本書結束時，您將獲得實用技能，能夠將這些技術應用於解決問題。無論您是希望提升職業生涯還是增強程式設計能力，本書提供了在快速發展的機器學習和神經網絡領域中脫穎而所需的工具和知識。

您將學到的內容：
- 掌握各種神經網絡拓撲的基本原理，包括DNN、RNN、LSTM、VAE、GAN和LLMs
- 使用最新版本的TensorFlow和Keras實現神經網絡，並提供詳細的Python代碼示例
- 知曉數據預處理、模型選擇和自定義的技術，以優化機器學習模型
- 在各種專業場景中應用機器學習和神經網絡技術

本書適合對象：
數據科學家、機器學習愛好者和希望加深對神經網絡和機器學習技術理解的軟體開發人員。

作者簡介

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.

作者簡介(中文翻譯)

Philip Hua 擁有超過 30 年的投資、風險管理和資訊科技經驗。他曾在對沖基金擔任合夥人，並在大型及精品公司領導風險和資訊科技部門，還共同創立了一家成功的金融科技公司。與 Paul Wilmott 博士一起，他開發了 CrashMetrics 方法論，這是一個評估投資組合中嚴重市場風險的重要工具。Philip 擁有倫敦帝國學院的應用數學博士學位、工商管理碩士學位以及工程學學士學位。

類似商品