This repository contains the code for Machine Learning with Python, by IBM CognitiveClass.
This is a hands-on course on Machine Learning using Python 3. The course focuses on the basics of Machine Learning using Python. The following topics are addressed:
- How Statistical Modelling relates to Machine Learning and do a comparison of each.
- Real-life examples of Machine learning and how it affects society in ways you may have guessed!
- Hands-on: Use Python Libraries for Machine Learning
The repository contains Jupyter Notebooks on the various algorithms and models:
- Popular algorithms: Regression, Classification, and Clustering
- Recommender Systems: Content-Based and Collaborative Filtering
- Popular models: Train/Test Split, Gradient Descent, and Mean Squared Error
The code samples have been tested using Python 3.7.3
- NumPy
- SciPy
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn
If you have an existing Python 3.7.x installation on a Unix-like system, you can install the above libraries using pip:
sudo -H python3 -m pip install <Library>
In case you are running Python 3.7.x on Windows use:
py -3 -m pip install <Library>
Alternatively, you can install Anaconda Distribution for your particular platform
anaconda.