AI Features

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All LessonsFree Lessons (3)

Course Overview

Introduction to Machine Learning

What Is Machine Learning?The Machine Learning Process What Is Scikit-Learn?Importing Data with Scikit-Learn Quiz: Introduction to Machine Learning Coding Challenge: Importing Data Solution: Importing Data

Preprocessing

Introduction to Preprocessing Feature Extraction Scaling Discretizing Encoding Dimensionality Reduction Imputation of Missing Values Quiz: Preprocessing Coding Challenge: Preprocessing Solution: Preprocessing

Supervised Learning

Introduction to Supervised Learning

Ensemble Methods

Quiz: Supervised Learning

Coding Challenge: Supervised Learning

Solution: Supervised Learning

Unsupervised Learning

Introduction to Unsupervised Learning GMM K-Means DBSCAN Hierarchical Clustering Quiz: Unsupervised Learning Coding Challenge: Unsupervised Learning Solution: Unsupervised Learning

Model Evaluation

Introduction to Model Evaluation Regression Metrics Classification Metrics Clustering Metrics Basic Cross-Validation Advanced Cross-Validation Quiz: Model Evaluation Coding Challenge: Model Evaluation Solution: Model Evaluation

Project

How to Predict the Traffic Volume Using Machine Learning

Tips and Tricks

Introduction to Tips and Tricks Pipelines Baselines Permutation Feature Importance Model Persistence Quiz: Tips and Tricks Coding Challenge: Tips and Tricks Solution: Tips and Tricks

Conclusion

Project

Customer Segmentation with K-Means Clustering

Scikit-Learn for Machine Learning

Solution: Supervised Learning

Follow the instructions for using supervised learning algorithms on preprocessed data.

We'll cover the following...

There are multiple possible solutions for this coding challenge, depending on the algorithms we choose, but here is one ...