Python Deep Learning Cookbook: Over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python
暫譯: Python 深度學習食譜：超過 75 個實用配方，涵蓋神經網絡建模、強化學習和轉移學習使用 Python

Indra den Bakker

Python Deep Learning Cookbook: Over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python

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商品描述

Key Features

  • Over 100 recipes on mathematical theory of each deep learning algorithm , its implementation and a bunch of related techniques for using them
  • Provides explanation with examples covering deep learning algorithms using popular python frameworks like TensorFlow, Caffe, Keras, Theano
  • Your ideal companion to train models involving neural networks problem and tuning it for a completely different problem, and getting impressive results.

Book Description

Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics.

The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras, Caffe or Theano is provided. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios.

What you will learn

  • Select the best Python framework for deep learning to use in case of specific problems/requirements
  • Understand the definition of neural network models
  • Learn to apply tips and tricks related to neural networks internals, to boost learning performances
  • Consolidate machine learning principles and apply them in the deep learning field
  • Reuse and adapt Python code snippets to everyday problems
  • Evaluate the cost/benefits and performance implication of each discussed solution

商品描述(中文翻譯)

#### 主要特點

- 超過 100 個關於每個深度學習演算法的數學理論、其實現及相關技術的食譜
- 提供使用流行的 Python 框架（如 TensorFlow、Caffe、Keras、Theano）涵蓋深度學習演算法的示例解釋
- 您理想的夥伴，用於訓練涉及神經網絡問題的模型，並調整其以解決完全不同的問題，並獲得令人印象深刻的結果。

#### 書籍描述

深度學習正在徹底改變各行各業。對於許多應用來說，深度學習已被證明能夠通過更快和更準確的預測超越人類。本書提供了自上而下和自下而上的方法，展示深度學習解決方案在不同領域的實際問題。這些應用包括計算機視覺、自然語言處理、時間序列和機器人技術。

《Python 深度學習食譜》針對所提出的問題提供技術解決方案，並詳細解釋這些解決方案。此外，還討論了使用流行框架（如 TensorFlow、PyTorch、Keras、Caffe 或 Theano）實施所提解決方案的相應優缺點。本書的主要目的是為 Python 程式設計師提供一個詳細的食譜列表，以將深度學習應用於常見和不太常見的場景。

#### 您將學到什麼

- 根據特定問題/需求選擇最佳的深度學習 Python 框架
- 理解神經網絡模型的定義
- 學習應用與神經網絡內部相關的技巧和竅門，以提升學習性能
- 鞏固機器學習原則並將其應用於深度學習領域
- 重用和調整 Python 代碼片段以解決日常問題
- 評估每個討論解決方案的成本/效益和性能影響

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