Python Artificial Intelligence Projects for Beginners
暫譯: 初學者的 Python 人工智慧專案

Joshua Eckroth

  • 出版商: Packt Publishing
  • 出版日期: 2018-07-31
  • 售價: $1,230
  • 貴賓價: 9.5$1,169
  • 語言: 英文
  • 頁數: 162
  • 裝訂: Paperback
  • ISBN: 1789539463
  • ISBN-13: 9781789539462
  • 相關分類: Python程式語言人工智慧
  • 海外代購書籍(需單獨結帳)

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商品描述

Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence.

This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.

By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress

What You Will Learn

  • Build a prediction model using decision trees and random forest
  • Use neural networks, decision trees, and random forests for classification
  • Detect YouTube comment spam with a bag-of-words and random forests
  • Identify handwritten mathematical symbols with convolutional neural networks
  • Revise the bird species identifier to use images
  • Learn to detect positive and negative sentiment in user reviews

商品描述(中文翻譯)

人工智慧(AI)是當前各種企業、行業和領域中最新的技術。 《Python 人工智慧專案入門》展示了使用 Python 的 AI 專案,涵蓋了構成人工智慧世界的現代技術。

本書首先幫助您使用流行的 Python 函式庫 scikit-learn 建立您的第一個預測模型。您將了解如何使用有效的機器學習技術——隨機森林(random forest)和決策樹(decision trees)來建立分類器。透過預測鳥類物種、分析學生表現數據、歌曲類型識別和垃圾郵件檢測等令人興奮的專案,您將學習這些智慧應用程式的基本原理以及各種算法和技術。在最後幾章中,您還將透過這些專案了解深度學習和神經網絡機制,並使用 Keras 函式庫的幫助。

在本書結束時,您將對使用 Python 建立自己的 AI 專案充滿信心,並準備在進步的過程中挑戰更高級的專案。

您將學到的內容:

- 使用決策樹和隨機森林建立預測模型
- 使用神經網絡、決策樹和隨機森林進行分類
- 使用詞袋模型和隨機森林檢測 YouTube 評論垃圾郵件
- 使用卷積神經網絡識別手寫數學符號
- 修改鳥類物種識別器以使用圖像
- 學習檢測用戶評論中的正面和負面情感

作者簡介

Joshua Eckroth

Joshua Eckroth is assistant professor of computer science at Stetson University, where he teaches big data mining and analytics, artificial intelligence (AI), and software engineering. Dr. Eckroth joined the math and computer science department at Stetson University in fall 2014. He earned his PhD from Ohio State University in AI and cognitive science, focusing on abductive reasoning and meta-reasoning.

作者簡介(中文翻譯)

### 約書亞·艾克羅斯 (Joshua Eckroth)

約書亞·艾克羅斯是斯特森大學(Stetson University)計算機科學的助理教授,教授大數據挖掘與分析、人工智慧(AI)以及軟體工程。艾克羅斯博士於2014年秋季加入斯特森大學的數學與計算機科學系。他在俄亥俄州立大學(Ohio State University)獲得人工智慧與認知科學的博士學位,專注於溯因推理(abductive reasoning)和元推理(meta-reasoning)。