Artificial Intelligence with Python (使用 Python 的人工智慧)
Prateek Joshi
- 出版商: Packt Publishing
- 出版日期: 2017-01-26
- 定價: $1,650
- 售價: 6.0 折 $990
- 語言: 英文
- 頁數: 446
- 裝訂: Paperback
- ISBN: 178646439X
- ISBN-13: 9781786464392
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相關分類:
Python、程式語言、人工智慧
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其他版本:
Artificial Intelligence with Python, 2/e (Paperback)
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相關主題
商品描述
Artificial Intelligence with Python: A Comprehensive Guide to Building Intelligent Apps for Python Beginners & Developers
Build real-world Artificial Intelligence applications to intelligently interact with the world around you, explore real-world scenarios, and learn about the various algorithms which can be used to build AI applications. Packed with insightful examples and topics such as predictive analytics and deep learning, this book is a must-have for Python developers.
Summary
Enter and explore the fascinating world of intelligent apps with Artificial Intelligence with Python. From deep learning through to clustering and predictive analytics, you’ll cover introductory and more advanced Artificial Intelligence topics, allowing you to create intelligent apps.
About the Technology
Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more.
About the Book
Starting with AI basics you’ll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
What’s Inside
- Cover the basics of Artificial Intelligence and dive into insightful examples
- Understand how to use different algorithms and build apps based on them
- Add intelligence layers to any apps based on various data
About the Reader
Ideal for Python developers who want to build real-world Artificial Intelligence applications, this book is accessible to Python beginners, and is also suitable for experienced Python programmers looking to use AI techniques in their existing technology stacks.
About the Author
Prateek Joshi is an artificial intelligence researcher, TEDx speaker, and published author of 5 books. Founder of venture-funded Silicon Valley startup Pluto AI, his work in the AI field has led to patents, tech demos and research papers. Prateek has worked for companies including Nvidia and Microsoft Research, and is a popular tech blogger and avid coder.
Table of Contents
- Introduction to Artificial Intelligence
- Classification and Regression Using Supervised Learning
- Predictive Analytics with Ensemble Learning
- Detecting Patterns with Unsupervised Learning
- Building Recommender Systems
- Logic Programming
- Heuristic Search Techniques
- Genetic Algorithms
- Building Games With Artificial Intelligence
- Natural Language Processing
- Probabilistic Reasoning for Sequential Data
- Building A Speech Recognizer
- Object Detection and Tracking
- Artificial Neural Networks
- Reinforcement Learning
- Deep Learning with Convolutional Neural Networks
商品描述(中文翻譯)
《Python人工智慧:建構智能應用程式的全面指南,適合Python初學者和開發者》
建構真實世界的人工智慧應用程式,與周遭環境智能互動,探索真實場景,並學習各種可用於建構人工智慧應用程式的演算法。本書充滿深入的例子和主題,如預測分析和深度學習,是Python開發者必備的工具。
【摘要】
進入並探索人工智慧與Python的迷人世界。從深度學習到分群和預測分析,您將涵蓋入門和更高級的人工智慧主題,讓您創建智能應用程式。
【關於技術】
人工智慧在現代世界中變得越來越重要。通過利用演算法的力量,您可以創建能夠智能互動世界的應用程式,建構智能推薦系統、自動語音識別系統等。
【關於本書】
從人工智慧基礎知識開始,您將學習如何使用數據挖掘技術開發基礎模塊。了解如何做出關於使用哪些演算法以及如何應用它們於真實場景的明智決策。本實用書籍涵蓋了多個主題,包括預測分析和深度學習。
【內容簡介】
- 涵蓋人工智慧基礎知識,並提供深入的例子
- 理解如何使用不同的演算法並基於它們構建應用程式
- 為任何基於各種數據的應用程式添加智能層
【讀者對象】
本書適合想要建構真實世界人工智慧應用程式的Python開發者,適合Python初學者,也適合有經驗的Python程序員希望在現有技術堆棧中使用人工智慧技術。
【關於作者】
Prateek Joshi是一位人工智慧研究員、TEDx演講者和出版的5本書的作者。他是風險投資的硅谷初創公司Pluto AI的創始人,他在人工智慧領域的工作已經取得了專利、技術演示和研究論文。Prateek曾在Nvidia和Microsoft Research等公司工作,是一位受歡迎的技術博客作者和熱衷的程式設計師。
【目錄】
1. 人工智慧簡介
2. 使用監督學習進行分類和回歸
3. 使用集成學習進行預測分析
4. 使用非監督學習檢測模式
5. 構建推薦系統
6. 邏輯編程
7. 啟發式搜索技術
8. 遺傳演算法
9. 使用人工智慧構建遊戲
10. 自然語言處理
11. 序列數據的概率推理
12. 構建語音識別器
13. 物體檢測和追蹤
14. 人工神經網絡
15. 強化學習
16. 使用卷積神經網絡進行深度學習