Introduction to Machine Learning with Scikit-Learn
Please bring a fully charged laptop
You dont need to have anything installed. We will be using Azure notebooks only. Please set up an account at notebooks.azure.com.
We will be using Python 3.
The lesson plan is as follows:
- Quick introduction to Azure Notebooks (10 Minutes)
- setting up a library
- creating an Azure notebook
- Markdown
- installing libraries
- Other useful libraries (i.e. pandas and numpy)
- Getting some data sets (5 Minutes)
- Pre-Instaled Datasets
- Uploading from local directory
- Uploading Datasets from github repositories.
- Clustering Example (10-15 Minutes)
- Quick example of clustering algorithm, using the iris data set
- Now you try:
- Regression Example (5-10 Minutes)
- Quick example of regression algorithm, using the ..... data set
- Now you try:
- Binary Classification Algorithm (5-10 Minutes)
- Quick example of Logistic Regression, using the SAhearts data set
- How good was our model? (10 Minutes)
- Confusion Matrices
- True Positive, True Negative
- Accuracy, Recall, Precision
- Class imbalance
- Random Forest (15 Minutes)
- Quick example of Random Forest algorithm, using the Titanic data set
- Now you try:
- Variable Importance
- Improving Your models (10 Minutes)
- Variable Transformation
- Feature Selection
- Missing data