Eder Santana's Deep Learning with Python
暫譯: Eder Santana 的 Python 深度學習

Eder Santana

  • 出版商: Packt Publishing
  • 出版日期: 2019-08-09
  • 售價: $1,530
  • 貴賓價: 9.5$1,454
  • 語言: 英文
  • 頁數: 156
  • 裝訂: Paperback
  • ISBN: 1787280462
  • ISBN-13: 9781787280465
  • 相關分類: Python程式語言DeepLearning
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Key Features

  • Covers the latest concepts in Python deep learning
  • Introduction to Tensorflow
  • Full of examples of solving complicated tasks

Book Description

Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python.

This book takes you from basic calculus knowledge to understanding backpropagation and its application for training in neural networks for deep learning and understanding automatic differentiation. Through the course, we will provide a thorough training in convolutional, recurrent neural networks and focus on supervised learning and integration into your product offerings such as search, image recognition, and object processing. We will also examine the performance of the sentimental analysis model and will conclude with an introduction to Tensorflow.

By the end of this book, you will be able to confidently start working with deep learning right away.

What you will learn

  • Get the lowdown on backpropagation
  • Perceive and understand automatic differentiation with Theano
  • Explore the powerful mechanism of seamless CPU and GPU usage with Theano
  • Apply convolutional neural networks for image analysis
  • Discover the methods of image classification and harness object recognition using deep learning
  • Get to know recurrent neural networks for the textual sentimental analysis model

商品描述(中文翻譯)

#### 主要特點

- 涵蓋 Python 深度學習的最新概念
- 介紹 Tensorflow
- 充滿解決複雜任務的範例

#### 書籍描述

深度學習目前是解決影像識別、語音識別、物體識別和自然語言問題的最佳方案之一,並且在 Python 中有越來越多的可用庫。

本書將帶您從基本的微積分知識開始,了解反向傳播及其在深度學習神經網絡訓練中的應用,並理解自動微分。通過這個課程,我們將提供對卷積神經網絡和遞迴神經網絡的全面訓練,並專注於監督式學習及其在您的產品中整合,例如搜尋、影像識別和物體處理。我們還將檢視情感分析模型的性能,並以介紹 Tensorflow 作為結尾。

在本書結束時,您將能夠自信地立即開始使用深度學習。

#### 您將學到的內容

- 瞭解反向傳播的詳細資訊
- 理解和掌握使用 Theano 的自動微分
- 探索 Theano 的無縫 CPU 和 GPU 使用的強大機制
- 應用卷積神經網絡進行影像分析
- 發現影像分類的方法並利用深度學習進行物體識別
- 了解用於文本情感分析模型的遞迴神經網絡