Deep Learning with Python: A Hands-on Introduction

Nikhil Ketkar

  • 出版商: Apress
  • 出版日期: 2017-04-19
  • 售價: $2,300
  • 貴賓價: 9.5$2,185
  • 語言: 英文
  • 頁數: 248
  • 裝訂: Paperback
  • ISBN: 1484227654
  • ISBN-13: 9781484227657
  • 相關分類: Python程式語言DeepLearning
  • 相關翻譯: Python深度學習 (簡中版)
  • 立即出貨 (庫存 < 3)

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商品描述

Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms.
 
This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included.
 
Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments. 
 
What You Will Learn 
  • Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe 
  • Gain the fundamentals of deep learning with mathematical prerequisites 
  • Discover the practical considerations of large scale experiments 
  • Take deep learning models to production
Who This Book Is For
 
Software developers who want to try out deep learning as a practical solution to a particular problem. Software developers in a data science team who want to take deep learning models developed by data scientists to production.

商品描述(中文翻譯)

這本書介紹了使用豐富的Python生態系統實施深度學習解決方案的實際方面。它填補了學術最新技術和行業最佳實踐之間的差距,介紹了Keras、Theano和Caffe等深度學習框架。這些框架的實際應用通常是通過閱讀源代碼、手冊和在社區論壇上發問來獲得的,這往往是一個緩慢而痛苦的過程。《Deep Learning with Python》讓您能夠在短時間內快速掌握這些實際知識,更加專注於領域、模型和算法。

本書簡要介紹了深度學習的數學先決條件和基礎知識,使其成為軟件開發人員入門深度學習的良好起點。書中還包括對深度學習架構的簡要調查。

《Deep Learning with Python》還向您介紹了自動微分和GPU計算的關鍵概念,雖然這些概念不是深度學習的核心,但在進行大規模實驗時至關重要。

您將學到什麼:
- 利用Python中的深度學習框架,即Keras、Theano和Caffe
- 獲得深度學習的基礎知識和數學先決條件
- 探索大規模實驗的實際考慮因素
- 將深度學習模型應用於生產環境

本書適合對於特定問題尋求深度學習實際解決方案的軟件開發人員,以及數據科學團隊中希望將數據科學家開發的深度學習模型應用於生產環境的軟件開發人員。