Introduction to Machine Learning

The course is held at FEI, VSB-TU Ostrava

Feel free to contact me (radek.svoboda@vsb.cz or office EA404, FEI) if you have any questions or want to discuss any topic from the course 😊

📊 Exercises

Exercise 1

The aim of the exercise is to get an overview of the basic capabilities of the Pandas, Matplotlib and Seaborn libraries and be able to setup a Python Virtual Enviroment (venv)

Jupyter Notebook

Google Colab

Exercise 2

The aim of the exercise is to learn basic techniques for visualization creation and interpretation using Matplotlib and Seaborn libraries.

Jupyter Notebook

Google Colab

More advanced concepts like subplots or correlation matrices can be found in Jupyter notebook below

Jupyter Notebook

Google Colab

💡 Notes

Cheat sheet for Pandas and Matplotlib/Seaborn

Jupyter Notebook

Google Colab

How to create a Python Virtual Enviroment named venv

Create venv

python -m venv venv

Activate venv

• Activate venv in Windows

.\venv\Scripts\Activate.ps1

• Activate venv in Linux

source venv/bin/activate

Intall python packages

pip install jupyter "jupyterlab>=3" "ipywidgets>=7.6"
pip install pandas matplotlib requests seaborn scipy scikit-learn

🚀 Run Jupyter lab

jupyter lab