Machine learning is what powers a data driven company. This course teaches you how to start creating your own models.
1 day
Professionals working with basic Python/Pandas knowledge who want to get started with Machine Learning
Learn how to train common supervised and unsupervised models, make predictions and assess their performance
In-classroom or virtual. The entire course is hands-on with lots of exercises involving machine learning models
Outline
Below is an example of how this course might be delivered. Of course this is fully customizable to fit your needs.
Audience
To follow this course, participants have to be familiar with the basics of Python as well as the Pandas library.
If your team does not have these skills, we can expand the scope of this course to include those.
Topics
- Machine Learning introduction
- Supervised vs Unsupervised learning
- Regression vs Classification
- Linear, Logistic and Polynomial Regression
- Measuring Regression Performance
- Classification with Naive Bayes
- Classification with Decision Tree
- Measuring Classification Performance
- K-means Clustering
- Cross Validation