Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications

Build smart applications by implementing real-world artificial intelligence projects




Key Features



  • Explore a variety of AI projects with Python


  • Get well-versed with different types of neural networks and popular deep learning algorithms


  • Leverage popular Python deep learning libraries for your AI projects





Book Description



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





Who this book is for



Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you're able to play around with code

1137616230
Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications

Build smart applications by implementing real-world artificial intelligence projects




Key Features



  • Explore a variety of AI projects with Python


  • Get well-versed with different types of neural networks and popular deep learning algorithms


  • Leverage popular Python deep learning libraries for your AI projects





Book Description



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





Who this book is for



Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you're able to play around with code

21.99 In Stock
Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications

Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications

by Dr. Joshua Eckroth
Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications

Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications

by Dr. Joshua Eckroth

eBook

$21.99 

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Overview

Build smart applications by implementing real-world artificial intelligence projects




Key Features



  • Explore a variety of AI projects with Python


  • Get well-versed with different types of neural networks and popular deep learning algorithms


  • Leverage popular Python deep learning libraries for your AI projects





Book Description



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





Who this book is for



Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you're able to play around with code


Product Details

ISBN-13: 9781789538243
Publisher: Packt Publishing
Publication date: 07/31/2018
Sold by: Barnes & Noble
Format: eBook
Pages: 162
File size: 18 MB
Note: This product may take a few minutes to download.

About the Author

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.
Dr. Joshua Eckroth is assistant professor of computer science at Stetson University, where he teaches artificial intelligence (AI), big data mining and analytics, and software engineering. He earned his PhD from The Ohio State University in AI and cognitive science. Dr. Eckroth also serves as Chief Architect at i2k Connect, which focuses on transforming documents into structured data using AI and enriched with subject matter expertise. Dr. Eckroth has previously published two video series with Packt, Python Artificial Intelligence Projects for Beginners and Advanced Artificial Intelligence Projects with Python. His academic publications may be found on Google Scholar.

Table of Contents

Table of Contents
  1. Building Your Own Prediction Models
  2. Prediction with Random Forests
  3. Application for comment classification
  4. Neural Networks
  5. Deep Learning
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