For people starting out with machine learning and looking to speed up their learning curve, this one-day hands-on course provides a solid structure to organize your thoughts as well as code snippets and best practices to get started. In this course you will learn to how to build, train, and evaluate machine learning models to predict continuous and discrete quantities using well tested and freely available Python libraries.
You Will Learn
- How to recognize problems that can be solved with machine learning
- How to decide the right technique (is it a classification problem? a regression? needs preprocessing?)
- How to load and manipulate data with Pandas
- How to visualize and explore data with Matplotlib
- How to build regression, classification, and clustering models with Scikit-Learn
- How to evaluate model performance with Scikit-Learn
Participants should download and install Miniconda Python 3.6 (https://conda.io/miniconda.html), and they should have access to the Internet during the workshop.