Intro to Machine Learning Labs
Lab 1: Intro to ML Packages: SKLearn
First, we'll walk through the linear classification in a sentiment analysis tutorial and cover how to build and tune models with SKLearn.
Next, we'll apply what you learned, and work through a news group excerise. We provide a sample solution in the news group solution.
Finally, we will walk through predicting continuous labels with a Linear regression tutorial from the Python Data Science Handbook.
Lab 2: Intro to DNN Packages: PyTorch
First, we'll walk through the MNIST tutorial together, and cover how to build and tune models on PyTorch. Next, you'll apply what you learned, and work through the CIFAR excercise yourself.
We provide a sample solution in the CIFAR solution.
Running the labs
The labs are Google Colaboratory notebooks, so just click the View in Colaboratory link on the notebook, and you should be all set!
To save your progress, you can copy the notebooks to your own google drive.
Requirements:
Software: A modern web browser. This has been tested on Google Chrome, Firefox, and Safari.
Accounts: A Google Account. If you don't have one, please make a free one.