Build a ML Classification Model in 12 Lines with PyCaret

Learn how to rapidly build a heart disease prediction model using PyCaret, a low-code machine learning library for Python. Follow along as the instructor demonstrates how to install PyCaret, load custom data from Kaggle using Pandas, and create an ML classification model with automated pipelines. Discover the power of PyCaret's state-of-the-art ML pipeline, which allows you to build and compare multiple models with just a few lines of code. By the end of this 22-minute tutorial, you'll have hands-on experience in prototyping a machine learning model for binary outcome prediction, including training, evaluating, testing, and saving your model.

- Start
- Gameplan
- How it Works
- 1. Install ad Import Dependencies
- 2. Load Data
- 3. Train and Evaluate Model
- 4. Test Model
- 5. Saving and Reload Models
- Wrap Up