WSL Linux Development Fundamentals

Traditional AI Development Pipeline#

# Data Collection & Processing

wget <https://dataset.com/data.csv>
python preprocess\_data.py --input data.csv --output clean\_data.csv

# Model Training

python train\_model.py --data clean\_data.csv --model transformer
python validate\_model.py --model saved\_model.pkl

# Deployment Preparation

docker build -t ai-model:latest .
docker run -p 8000:8000 ai-model:latest

# Production Deployment

ssh user@production-server
docker pull ai-model:latest
docker-compose up -d

Why This Requires Linux Skills#

• Package Management: Installing Python, CUDA, and AI libraries
• File Permissions: Managing data and model files securely
• Process Management: Running long training jobs
• Network Configuration: Setting up APIs and services
• Resource Monitoring: Tracking GPU and memory usage