Get up and running with Artificial Intelligence through 8 exciting and practical AI applications
Artificial Intelligence (AI) is rapidly transforming industries, businesses, and everyday life.
This repository/book, Python Artificial Intelligence Projects for Beginners, walks you through hands-on AI projects built with Python.
Each project demonstrates modern AI techniques and their real-world applications, helping you gain practical experience in the field.
Through these projects, you will learn how to:
- Build a prediction model using Decision Trees and Random Forests
- Apply Neural Networks, Decision Trees, and Random Forests for classification tasks
- Detect YouTube comment spam using Bag-of-Words and Random Forests
- Recognize handwritten mathematical symbols with Convolutional Neural Networks (CNNs)
This book is designed for Python developers who want to take their first steps into Artificial Intelligence through guided, easy-to-follow projects.
- Prerequisites: Basic knowledge of Python programming is recommended
- No prior AI/ML experience is required
You’ll be able to follow along, experiment with the code, and adapt the projects for your own learning and applications.
To run the code files provided (Chapters 1–5), ensure the following setup:
| Chapter | Software Required | OS Required |
|---|---|---|
| 1–5 | Python 3.4 or later | Windows 7+, macOS 10.10+, or Linux (with at least 4 GB RAM) |
This repository includes several real-world inspired AI projects that you can build and extend:
- Student Performance Prediction – Predict student outcomes using decision trees and random forests
- Bird Identifier – Classify bird species with image recognition models
- Sentiment Analysis – Analyze text data to determine sentiment (positive, negative, neutral)
- Sentiment Analysis (Enhanced) – A more advanced sentiment analysis with deeper NLP techniques
- Spam Detector – Detect spam messages or comments using Bag-of-Words and Random Forests
- Genre Identifier – Classify music or text into different genres using machine learning
- Birds Custom CNN – Build a custom Convolutional Neural Network to classify bird images
By the end of this journey, you will have built working AI applications in Python, gaining both theoretical knowledge and practical implementation skills that can serve as a foundation for more advanced AI projects.