Machine Learning with Python
Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This free Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning.Start the Free Course
About this Course
This Machine Learning with Python course dives into the basics of Machine Learning using Python, an approachable and well-known programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
Look at real-life examples of Machine Learning and how it affects society in ways you may not have guessed!
Explore many algorithms and models:
- Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction.
- Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests.
More important, you will transform your theoretical knowledge in to practical skill using many hands-on labs.
Get ready to do more learning than your machine!
Module 1 - Introduction to Machine Learning
- Applications of Machine Learning
- Supervised vs Unsupervised Learning
- Python libraries suitable for Machine Learning
Module 2 - Regression
- Linear Regression
- Non-linear Regression
- Model evaluation methods
Module 3 - Classification
- K-Nearest Neighbour
- Decision Trees
- Logistic Regression
- Support Vector Machines
- Model Evaluation
Module 4 - Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- Density-Based Clustering
Module 5 - Recommender Systems
- Content-based recommender systems
- Collaborative Filtering
Prerequisites for this course
Recommended skills prior to taking this course
- You have to do hands-on lab for this course. The tool that you use for hands-on is called JupyterLab and it is one of the most popular tools used by data scientists. If you are not familiar with JupyterLab, I would recommend that you take our free Data Science Hands-on with Open Source Tools.
- This hands-on lab requires that you have working knowledge of Python programming language as it applies to data analytics. If you don't feel you have sufficient skill in Data Analysis with Python, I recommend you take Data Analysis with Python courses.
Saeed Aghabozorgi, PhD is a Sr. Data Scientist in IBM with a track record of developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowledge. He is a researcher in data mining field and expert in developing advanced analytic methods like machine learning and statistical modelling on large datasets.
The following individual also contributed: Agatha Colangelo