microsoft/AI-For-Beginners
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examples/README.md
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| 1 | # Beginner-Friendly AI Examples |
| 2 | |
| 3 | 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. |
| 4 | |
| 5 | ## 📚 Examples Overview |
| 6 | |
| 7 | | Example | Description | Difficulty | Prerequisites | |
| 8 | |---------|-------------|------------|---------------| |
| 9 | | [Hello AI World](./01-hello-ai-world.py) | Your first AI program - simple pattern recognition | ⭐ Beginner | Python basics | |
| 10 | | [Simple Neural Network](./02-simple-neural-network.py) | Build a neural network from scratch | ⭐⭐ Beginner+ | Python, basic math | |
| 11 | | [Image Classifier](./03-image-classifier.ipynb) | Classify images with a pre-trained model | ⭐⭐ Beginner+ | Python, numpy | |
| 12 | | [Text Sentiment](./04-text-sentiment.py) | Analyze text sentiment (positive/negative) | ⭐⭐ Beginner+ | Python | |
| 13 | |
| 14 | ## 🚀 Getting Started |
| 15 | |
| 16 | ### Prerequisites |
| 17 | |
| 18 | Make sure you have Python installed (3.8 or higher recommended). Install required packages: |
| 19 | |
| 20 | ```bash |
| 21 | # For Python scripts |
| 22 | pip install numpy |
| 23 | |
| 24 | # For Jupyter notebooks (image classifier) |
| 25 | pip install jupyter numpy pillow tensorflow |
| 26 | ``` |
| 27 | |
| 28 | Or use the conda environment from the main curriculum: |
| 29 | |
| 30 | ```bash |
| 31 | conda env create --name ai4beg --file ../environment.yml |
| 32 | conda activate ai4beg |
| 33 | ``` |
| 34 | |
| 35 | ### Running the Examples |
| 36 | |
| 37 | **For Python scripts (.py files):** |
| 38 | ```bash |
| 39 | python 01-hello-ai-world.py |
| 40 | ``` |
| 41 | |
| 42 | **For Jupyter notebooks (.ipynb files):** |
| 43 | ```bash |
| 44 | jupyter notebook 03-image-classifier.ipynb |
| 45 | ``` |
| 46 | |
| 47 | ## 📖 Learning Path |
| 48 | |
| 49 | We recommend following the examples in order: |
| 50 | |
| 51 | 1. **Start with "Hello AI World"** - Learn the basics of pattern recognition |
| 52 | 2. **Build a Simple Neural Network** - Understand how neural networks work |
| 53 | 3. **Try the Image Classifier** - See AI in action with real images |
| 54 | 4. **Analyze Text Sentiment** - Explore natural language processing |
| 55 | |
| 56 | ## 💡 Tips for Beginners |
| 57 | |
| 58 | - **Read the code comments carefully** - They explain what each line does |
| 59 | - **Experiment!** - Try changing values and see what happens |
| 60 | - **Don't worry about understanding everything** - Learning takes time |
| 61 | - **Ask questions** - Use the [Discussion board](https://github.com/microsoft/AI-For-Beginners/discussions) |
| 62 | |
| 63 | ## 🔗 Next Steps |
| 64 | |
| 65 | After completing these examples, explore the full curriculum: |
| 66 | - [Introduction to AI](../lessons/1-Intro/README.md) |
| 67 | - [Neural Networks](../lessons/3-NeuralNetworks/README.md) |
| 68 | - [Computer Vision](../lessons/4-ComputerVision/README.md) |
| 69 | - [Natural Language Processing](../lessons/5-NLP/README.md) |
| 70 | |
| 71 | ## 🤝 Contributing |
| 72 | |
| 73 | Found these examples helpful? Help us improve them: |
| 74 | - Report issues or suggest improvements |
| 75 | - Add more examples for beginners |
| 76 | - Improve documentation and comments |
| 77 | |
| 78 | --- |
| 79 | |
| 80 | *Remember: Every expert was once a beginner. Happy learning! 🎓* |