Python Artificial Intelligence Projects for Beginners
Joshua Eckroth
- 出版商: Packt Publishing
- 出版日期: 2018-07-31
- 售價: $1,000
- 貴賓價: 9.5 折 $950
- 語言: 英文
- 頁數: 162
- 裝訂: Paperback
- ISBN: 1789539463
- ISBN-13: 9781789539462
-
相關分類:
Python、人工智慧
下單後立即進貨 (約3~4週)
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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
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.