https://linkedin.com/in/dennisbakhuis/

For a tutorial session I created this Jupyter Notebook in which I try to explain the concepts of a Logistic Regression and the related Linear Regression. These are than first coded in Tensorflow and later recreated using Numpy. Feel free to use the material, ask questions, send comments, or just a thank you message.

• a working anaconda / miniconda environment.
• a shell (powershell / bash / or equivalent)

1. open a shell
2. conda create --name tutor python=3.7
3. conda activate tutor
4. pip install tensorflow pandas jupyterlab matplotlib
   (for completeness, I also provided a requirements.txt, but the above should work.)

1. jupyter lab
2. In jupyter lab, open the notebook named: Logistic_Regression.ipynb