Introduction to Tips and Tricks
Explore practical tips and tricks in scikit-learn to streamline your machine learning workflow. Learn how to use pipelines for consistent preprocessing, analyze feature importance to improve models, save and load models efficiently, and establish baseline models for performance comparison.
We'll cover the following...
We'll cover the following...
The scikit-learn library includes a wide range of tools for ML, and many of them go beyond preprocessing data and training ML models.
Let’s get a quick overview of some of the most useful tools: pipelines, baselines, feature importance, and model persistence.
The power of pipelines
Pipelines are a fundamental concept in scikit-learn that allow us to streamline and organize our ML workflow. A pipeline combines multiple data ...