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:
Would you like to understand how and why machine learning techniques and data analytics are spearheading enterprises globally? From analyzing bioinformatics to predicting climate change, machine learning plays an increasingly pivotal role in our society.
Although the real-world applications may seem complex, The Supervised Learning Workshop simplifies supervised learning for beginners with a step-by-step interactive approach. Working with real-time datasets, you’ll learn how supervised learning, when used with Python, can produce efficient predictive models.
- Import NumPy and pandas libraries to assess the data in a Jupyter Notebook
- Discover patterns within a dataset using exploratory data analysis
- Use pandas to find the summary statistics of a dataset
- Improve the performance of a model with linear regression analysis
- Increase the prediction 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: