Welcome! This directory contains simple, standalone examples to help you get started with AI and machine learning. Each example is designed to be beginner-friendly with detailed comments and step-by-step explanations.
| Example | Description | Difficulty | Prerequisites |
|---|---|---|---|
| Hello AI World | Your first AI program - simple pattern recognition | β Beginner | Python basics |
| Simple Neural Network | Build a neural network from scratch | ββ Beginner+ | Python, basic math |
| Image Classifier | Classify images with a pre-trained model | ββ Beginner+ | Python, numpy |
| Text Sentiment | Analyze text sentiment (positive/negative) | ββ Beginner+ | Python |
Make sure you have Python installed (3.8 or higher recommended). Install required packages:
# For Python scripts
pip install numpy
# For Jupyter notebooks (image classifier)
pip install jupyter numpy pillow tensorflowOr use the conda environment from the main curriculum:
conda env create --name ai4beg --file ../environment.yml
conda activate ai4begFor Python scripts (.py files):
python 01-hello-ai-world.pyFor Jupyter notebooks (.ipynb files):
jupyter notebook 03-image-classifier.ipynbWe recommend following the examples in order:
- Start with "Hello AI World" - Learn the basics of pattern recognition
- Build a Simple Neural Network - Understand how neural networks work
- Try the Image Classifier - See AI in action with real images
- Analyze Text Sentiment - Explore natural language processing
- Read the code comments carefully - They explain what each line does
- Experiment! - Try changing values and see what happens
- Don't worry about understanding everything - Learning takes time
- Ask questions - Use the Discussion board
After completing these examples, explore the full curriculum:
Found these examples helpful? Help us improve them:
- Report issues or suggest improvements
- Add more examples for beginners
- Improve documentation and comments
Remember: Every expert was once a beginner. Happy learning! π