Python Deep Learning (Paperback)

Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter Roelants

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商品描述

Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.

About This Book

  • Explore and create intelligent systems using cutting-edge deep learning techniques
  • Implement deep learning algorithms and work with revolutionary libraries in Python
  • Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more

Who This Book Is For

This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.

What You Will Learn

  • Get a practical deep dive into deep learning algorithms
  • Explore deep learning further with Theano, Caffe, Keras, and TensorFlow
  • Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines
  • Dive into Deep Belief Nets and Deep Neural Networks
  • Discover more deep learning algorithms with Dropout and Convolutional Neural Networks
  • Get to know device strategies so you can use deep learning algorithms and libraries in the real world

In Detail

With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.

The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.

Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.

Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.

Style and approach

Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.

商品描述(中文翻譯)

將您的機器學習技能提升到更高的水平,通過使用Python掌握深度學習的概念和算法。

關於本書

- 使用尖端的深度學習技術探索和創建智能系統
- 在Python中實現深度學習算法並使用革命性的庫
- 獲得Theano、TensorFlow、H2O等的實際示例和易於跟隨的教程

本書適合對機器學習概念有基本基礎理解並具有一些Python編程經驗的數據科學從業者和有志者。具備對微積分和統計概念的概念性理解的數學背景也是理想的。

您將學到什麼

- 深入了解深度學習算法
- 進一步探索Theano、Caffe、Keras和TensorFlow等深度學習
- 了解兩種在許多實際深度學習實現的核心技術:自編碼器和受限玻爾茨曼機
- 深入研究深度信念網絡和深度神經網絡
- 通過Dropout和卷積神經網絡了解更多深度學習算法
- 了解設備策略,以便在現實世界中使用深度學習算法和庫

詳細內容

隨著全球對人工智能的興趣日益增加,深度學習引起了廣泛的公眾關注。每天,深度學習算法在不同行業中被廣泛應用。

本書將為您提供有關該主題的所有實用信息,包括最佳實踐和使用實際用例。您將學習識別和提取信息以提高預測準確性並優化結果。

從快速回顧重要的機器學習概念開始,本書將直接深入深度學習原則,使用Sci-kit learn。隨著進一步的學習,您將學習使用最新的開源庫,如Theano、Keras、Google的TensorFlow和H20。使用本指南來揭示模式識別的困難,以更高的準確性擴展數據並討論深度學習算法和技術。

無論您是想深入研究深度學習,還是想研究如何更好地利用這項強大的技術,您都能在本書中找到一切。

風格和方法

《Python機器學習實例》遵循實用的實踐方法。它通過真實世界的項目,引導您了解Python的關鍵元素和其強大的機器學習庫。