This repository contains the code and materials for the course "Python Essentials for MLOps" offered by AI Core. The course covers the basics of Python programming, data structures, algorithms, object-oriented programming, testing, debugging, and packaging. The course also introduces some useful Python libraries and frameworks for machine learning operations (MLOps), such as NumPy, pandas, scikit-learn, TensorFlow, Keras, PyTorch, Streamlit, and MLflow.
• notebooks: This folder contains the Jupyter notebooks for each lesson of the course. The notebooks include the lecture slides, code examples, exercises, and solutions.
• src: This folder contains the Python scripts for some of the code examples and exercises in the notebooks.
• data: This folder contains the data files used in the notebooks and scripts.
• requirements.txt: This file lists the Python packages required to run the notebooks and scripts.
To use this repository, you need to have Python 3.6 or higher installed on your machine. You can download Python from here.
You also need to install the required packages using the following command:
pip install -r requirements.txt
Alternatively, you can create a virtual environment using conda or venv and install the packages there.
To run the notebooks, you need to launch Jupyter Notebook or Jupyter Lab from the root directory of the repository using the following commands:
jupyter notebook
or
jupyter lab
Then you can navigate to the notebooks folder and open the notebook of your choice.
To run the scripts, you can use any Python IDE or editor of your choice, or run them from the command line using the following syntax:
python scripts/<script_name>.py
This repository is licensed under the Apache-2.0 License.