Getting Started

This guide will help you get started with AI-Practices.

Prerequisites

Component	Minimum	Recommended
Python	3.10	3.10 ~ 3.11
CPU	4 cores	8+ cores
RAM	8 GB	32 GB
GPU	GTX 1060	RTX 3080+
Storage	50 GB	200 GB SSD

Installation

1. Clone Repository

git clone https://github.com/zimingttkx/AI-Practices.git
cd AI-Practices

2. Create Environment

conda create -n ai-practices python=3.10 -y
conda activate ai-practices

3. Install Dependencies

pip install -r requirements.txt

4. Verify Installation

python -c "import tensorflow as tf; print(f'TensorFlow: {tf.__version__}')"
python -c "import torch; print(f'PyTorch: {torch.__version__}')"

5. Launch Jupyter

jupyter lab

Run First Experiment

cd 09-practical-projects/02-computer-vision/01-mnist-cnn
python src/train.py --epochs 20 --batch_size 64

Expected Output:

Epoch 20/20 - loss: 0.0234 - accuracy: 0.9921
Test Accuracy: 99.12%

Learning Path

Beginner (8-12 weeks)

Week 1-2:  01-foundations (Part 1)
Week 3-4:  01-foundations (Part 2)
Week 5-6:  02-neural-networks
Week 7-8:  03-computer-vision
Week 9-10: 04-sequence-models
Week 11-12: 09-practical-projects

Advanced (4-6 weeks)

Week 1-2: 05-advanced-topics
Week 3-4: 06-generative-models
Week 5-6: 07-reinforcement-learning

Next Steps

• Installation - Detailed installation guide
• Architecture - System architecture
• Module 01 - Start learning