This is the repository for The Supervised Learning Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish.

To get started with the project files, you'll need to:

1. Install Jupyter on Windows, Mac, Linux
2. Install Anaconda on Windows, Mac, Linux

Taking an engaging and practical approach, The Supervised Learning Workshop teaches you how to predict the output of new data, based on the relationship and behavior of existing datasets. You’ll learn at your own pace and use Python libraries and Jupyter to build intelligent predictive models.  

• Import NumPy and pandas libraries to assess the data in a Jupyter Notebook
• Discover patterns within a dataset using exploratory data analysis
• Using pandas to find the summary statistics of a dataset
• Improve the performance of a model with linear regression analysis
• Increase the predictive accuracy with decision trees such as k-nearest neighbor (KNN) models
• Plot precision-recall and ROC curves to evaluate model performance

If you've found this repository useful, you might want to check out some of our other workshop titles:

• The Unsupervised Learning Workshop
• The Reinforcement Learning Workshop
• The Applied AI and Natural Language Processing Workshop