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All LessonsFree Lessons (4)

Preliminaries

Introduction Prerequisites

Working with Datasets

Load built-in dataset Generate synthetic dataset Data Preprocessing

Feature Engineering

Feature Selection Feature Extraction Missing Value PCA(Principal Component Analysis)Pipeline

General Concepts

Parameter Searching

Linear Regression

Linear Regression Challenge - Auto Insurance Prediction Challenge Solution Review

Logistic Regression

Logistic Regression Challenge - Classification Prediction With Data Preprocessing Challenge Solution Review

Support Vector Machine

Support Vector Machine Challenge - Classification of non-linear data Challenge Solution Review

Tree Model and Ensemble Method

Decision Tree Gradient Boosting Tree Challenge - GBDT Parameter Fine-Tune Challenge Solution Review Random Forest

Unsupervised Learning

K-means Clustering t-SNE

Deep Learning

Neural Network Challenge - Build a Neural Network and fine-tune it Challenge Solution Review

Others

KNN (K-Nearest Neighbors)

What's Next

Hands-on Machine Learning with Scikit-Learn/

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Quiz

Quiz

We'll cover the following...

Technical Quiz

1.

Is it true that we need to scale our feature values when they vary greatly?

A.

True

B.

False

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