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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 Linear Models SVM SGD KNN Decision Trees Naive Bayes 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/

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Solution: Importing Data

Solution: Importing Data

Follow the instructions for importing data from a CSV file.

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As the import pandas as pd code indicates, one possible solution to this challenge is to use pandas to read our csv file:

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Python 3.8

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