[Course][Udemy][Gourav Shah] DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End [ENG, 2025]

Git
https://github.com/mlopsbootcamp/house-price-predictor

Делаю:
2025.06.15

03. Use Case and Environment Setup

06. Launching MLflow for Experiemnt Tracking

$ mkdir -p ~/projects/courses/mlops
$ cd ~/projects/courses/mlops/house-price-predictor/

$ git clone [email protected]:webmakaka/house-price-predictor.git
$ cd house-price-predictor/deployment/mlflow/
$ docker compose up

// OK!
http://localhost:5555

08. Setting up Python Virtual Environment with UV

$ curl -LsSf https://astral.sh/uv/install.sh | sh
$ uv venv --python python3.11
$ source .venv/bin/activate

$ uv pip install -r requirements.txt

09. Working with Jupyter Notebooks

$ code .

^P

ext install ms-toolsai.jupyter

04. From Data to Models - Understanding Data Science with Feature Engineering

02. Learning Data Engineering

$ python src/data/run_processing.py   --input data/raw/house_data.csv   --output data/processed/cleaned_house_data.csv

06. Preparing for Model Experimentation

$ python src/features/engineer.py   --input data/processed/cleaned_house_data.csv   --output data/processed/featured_house_data.csv   --preprocessor models/trained/preprocessor.pkl