Learning Scikit-Learn by Example

This repo is a collection of exercises I have undergone in order to

test and experiment with sklearn's capability
try commands to see what the output is and how to use it for next steps
learn various models
learn enhacements such as regularization
put together various ensemble models

Table of Contents

Models
- Regression
- Classification
Performance Tuning
Ensemble Models
Misc Tutorials & Exercises

Models

Regression

Classification

Gaussian Naive Bayes

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!

Repository files navigation

Learning Scikit-Learn by Example

Models

Regression

Classification

Performance Tuning

Ensembles

Misc Tutorials & Exerices

About

Uh oh!

Releases

Packages

Languages

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
.ipynb_checkpoints		.ipynb_checkpoints
datasets		datasets
img		img
.DS_Store		.DS_Store
Automating Pipeline (Using Sklearn AutoML - Analyzing with PipelineProfiler).ipynb		Automating Pipeline (Using Sklearn AutoML - Analyzing with PipelineProfiler).ipynb
Boosting - AdaBoost.ipynb		Boosting - AdaBoost.ipynb
Boosting - Gradient Boosting.ipynb		Boosting - Gradient Boosting.ipynb
Classifying Blobs (Gaussian naive Bayes Classification).ipynb		Classifying Blobs (Gaussian naive Bayes Classification).ipynb
Classifying Cancer (Support Vector Machines).ipynb		Classifying Cancer (Support Vector Machines).ipynb
Classifying Digits (K-Means).ipynb		Classifying Digits (K-Means).ipynb
Classifying Digits (Scikit-Learn - MNIST data classification).ipynb		Classifying Digits (Scikit-Learn - MNIST data classification).ipynb
Classifying Iris Flower (KNN Algorithm).ipynb		Classifying Iris Flower (KNN Algorithm).ipynb
Classifying Iris Flower (Support Vector Machine - Linear).ipynb		Classifying Iris Flower (Support Vector Machine - Linear).ipynb
Classifying Iris Flowers (Decision Tree - Scikit).ipynb		Classifying Iris Flowers (Decision Tree - Scikit).ipynb
Classifying Moons (Support Vector Machine - Non-Linear).ipynb		Classifying Moons (Support Vector Machine - Non-Linear).ipynb
Classifying Text (Gaussian Multinomial Naive Bayes).ipynb		Classifying Text (Gaussian Multinomial Naive Bayes).ipynb
Ensemble - Random Forest.ipynb		Ensemble - Random Forest.ipynb
Ensemble Model - Bagging and Pasting.ipynb		Ensemble Model - Bagging and Pasting.ipynb
Ensemble Model - Voting (Scikit).ipynb		Ensemble Model - Voting (Scikit).ipynb
Extracting Feature Importance from Random Forest.ipynb		Extracting Feature Importance from Random Forest.ipynb
Predicting Bicycle Traffic (Regression).ipynb		Predicting Bicycle Traffic (Regression).ipynb
Predicting Home Prices (Decision Tree - Optimizing Model).ipynb		Predicting Home Prices (Decision Tree - Optimizing Model).ipynb
Predicting Home Prices (Decision Tree).ipynb		Predicting Home Prices (Decision Tree).ipynb
Predicting Home Prices (Multiple Variable Linear Regression).ipynb		Predicting Home Prices (Multiple Variable Linear Regression).ipynb
Predicting Home Prices (Single Variable Linear Regression).ipynb		Predicting Home Prices (Single Variable Linear Regression).ipynb
Predicting Moons (Regression using Decision Tree - Scikit).ipynb		Predicting Moons (Regression using Decision Tree - Scikit).ipynb
README.md		README.md
Stacking with Digits Dataset.ipynb		Stacking with Digits Dataset.ipynb

joshuamschultz/learning-scikit-learn

Folders and files

Latest commit

History

Repository files navigation

Learning Scikit-Learn by Example

Models

Regression

Classification

Performance Tuning

Ensembles

Misc Tutorials & Exerices

About

Topics

Resources

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Languages

Packages