Level: Intermediate to Advanced
Prerequisite: Students must set up their laptops in advance
Python is one of the most popular languages used in machine learning, data science, and predictive analytics. In this hands-on course, you will how to use Python, scikit-learn, and lightgbm to create regression and decision tree models. You will leave with complete code examples that you can use and build on in your own work.
You Will Learn
- What a classification model is and how to train two types (logistic regression and decision tree classifiers)
- What a regression model is and how to train two types (linear regression and neural networks)
- How to perform feature engineering and why it is important
- How to properly set up a training, cross-validation, and testing workflow
- How to guard against overfitting with regularization and hyper-parameters
Geared To
- Individuals with basic Python experience who are new to using Python for data analysis
Laptop Setup
Students must bring their own laptop to the class.
Machine Requirements:
- Linux, OS X, or Windows
- 32- or 64-bit computer
- 8 MB available RAM
- 600 MB available hard drive space to download and install Anaconda
(We use Anaconda because it is a free, no-hassle way to install Python and the needed libraries.)
Setup:
Laptop setup is required BEFORE the conference. Instructions will be emailed to registrants prior to the event.
There is no time allotted in class for laptop preparation.
* Enrollment is limited to 40 attendees.