Deep Learning for Beginners: A comprehensive introduction of deep learning fundamentals for beginners to understanding frameworks, neural networks,
暫譯: 初學者的深度學習:深度學習基礎的全面介紹,幫助初學者理解框架與神經網絡

Cooper, Steven

  • 出版商: Data Science
  • 出版日期: 2019-07-30
  • 售價: $840
  • 貴賓價: 9.5$798
  • 語言: 英文
  • 頁數: 188
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3903331074
  • ISBN-13: 9783903331075
  • 相關分類: DeepLearning
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

If you are looking for a complete beginners guide to learn deep learning with examples, in just a few hours, then you need to continue reading.

This book delves into the basics of deep learning for those who are enthusiasts concerning all things machine learning and artificial intelligence. For those who have seen movies which show computer systems taking over the world like, Terminator, or benevolent systems that watch over the population, i.e. Person of Interest, this should be right up your alley.

This book will give you the basics of what deep learning entails. That means frameworks used by coders and significant components and tools used in deep learning, that enable facial recognition, speech recognition, and virtual assistance. Yes, deep learning provides the tools through which systems like Siri became possible.

Grab your copy today and learn:

  • Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues. TensorFlow is the most popular tool and is used by corporate giants such as Airbus, Twitter, and even Google.
  • The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook. Facebook illustrates Caffe2 as one of the lightweight and modular deep learning frameworks, though TensorFlow is the most popular one, considering it has a lot of popularity, and thus, a big forum, which allows for assistance on main problems.
  • The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders. These algorithms create the building blocks which propel deep learning and advance it.
  • The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity. The Internet of Things is also represented here, as deep learning allows for integration of various systems via an artificial intelligence system, which is already being used for the home and car functions.
  • And much more...

The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow.

This book is probably one of the best books for beginners. It's a step-by-step guide for any person who wants to start learning deep learning and artificial intelligence from scratch.

When data science can reduce spending costs by billions of dollars in our economy, why wait to jump in?

商品描述(中文翻譯)

如果您正在尋找一本完整的初學者指南,以便在幾小時內學習深度學習並附有範例,那麼您需要繼續閱讀。

本書深入探討深度學習的基本概念,適合對機器學習和人工智慧充滿熱情的人士。對於那些看過像《終結者》這樣的電影,展示電腦系統接管世界,或是像《疑犯追蹤》這樣的電影,展示善意系統監控人群的人來說,這本書將非常合適。

本書將為您提供深度學習的基本知識。這意味著將介紹程式設計師使用的框架,以及在深度學習中用於臉部識別、語音識別和虛擬助手的主要組件和工具。是的,深度學習提供了使得像 Siri 這樣的系統成為可能的工具。

今天就來獲取您的副本,學習:

- 深度學習利用框架,讓人們能夠開發出能夠提供更好抽象和簡化困難程式設計問題的工具。TensorFlow 是最受歡迎的工具,並被空中巴士、Twitter 甚至 Google 等企業巨頭使用。
- 本書將 TensorFlow 和 Caffe2 描述為 Google 和 Facebook 用於開發的主要框架。Facebook 將 Caffe2 描述為一種輕量級和模組化的深度學習框架,儘管 TensorFlow 是最受歡迎的,因為它擁有大量的使用者和論壇,能夠提供主要問題的協助。
- 本書考慮了深度學習的幾個組件和工具,例如神經網絡;CNN、RNN、GAN 和自編碼器。這些算法創造了推動深度學習和促進其進步的基礎構件。
- 本書還考慮了幾個應用,包括聊天機器人和虛擬助手,這些已成為未來深度學習的主要焦點,因為它們代表了信息收集和連接的下一個前沿。物聯網在這裡也有所體現,因為深度學習允許通過人工智慧系統整合各種系統,這已經在家庭和汽車功能中得到應用。
- 還有更多...

數據科學的使用為企業增添了許多價值,我們將持續看到對數據科學家的需求增長。

這本書可能是初學者最好的書籍之一。它是一本逐步指南,適合任何想從零開始學習深度學習和人工智慧的人。

當數據科學能夠在我們的經濟中減少數十億美元的支出時,為什麼還要等著跳進來呢?