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https://github.com/packtworkshops/the-machine-learning-workshop

An interactive approach to understanding Machine Learning using scikit-learn
https://github.com/packtworkshops/the-machine-learning-workshop

artificial-neural-networks calinski-harabaz-score dbscan-clustering k-means-clustering mean-shift naive-bayes-algorithm silhouette-score support-vector-machine

Last synced: 5 days ago
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An interactive approach to understanding Machine Learning using scikit-learn

Host: GitHub
URL: https://github.com/packtworkshops/the-machine-learning-workshop
Owner: PacktWorkshops
License: mit
Created: 2020-01-10T11:29:25.000Z (almost 5 years ago)
Default Branch: master
Last Pushed: 2022-06-22T02:13:27.000Z (over 2 years ago)
Last Synced: 2024-02-06T05:45:19.500Z (9 months ago)
Topics: artificial-neural-networks, calinski-harabaz-score, dbscan-clustering, k-means-clustering, mean-shift, naive-bayes-algorithm, silhouette-score, support-vector-machine
Language: Jupyter Notebook
Homepage:
Size: 10.1 MB
Stars: 27
Watchers: 5
Forks: 45
Open Issues: 1
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # The Machine Learning Workshop

[![GitHub issues](https://img.shields.io/github/issues/PacktWorkshops/The-Machine-Learning-Workshop.svg)](https://github.com/PacktWorkshops/The-Machine-Learning-Workshop/issues)

[![GitHub forks](https://img.shields.io/github/forks/PacktWorkshops/The-Machine-Learning-Workshop.svg)](https://github.com/PacktWorkshops/The-Machine-Learning-Workshop/network)

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[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](https://github.com/PacktWorkshops/The-Machine-Learning-Workshop/pulls)

This is the repository for [The Machine Learning Workshop](https://www.amazon.com/Machine-Learning-Workshop-high-performance-scikit-learn/dp/1839219068/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1611061956&sr=1-1&utm_source=github&utm_medium=repository&utm_campaign=9781801070065&utm_term=Machine%20Learning&utm_content=The%20Machine%20Learning%20Workshop), published by [Packt](https://www.packtpub.com/?utm_source=github). It contains all the supporting project files necessary to work through the course from start to finish.

## Requirements and Setup



To get started with the project files, you'll need to:

1. Install Python on [Windows/Mac](https://www.python.org/downloads/release/python-376/)

2. Install pip on [Windows/Mac/Linux](https://pip.pypa.io/en/stable/installing/)

## About The Machine Learning Workshop

With expert guidance and real-world examples, [The Machine Learning Workshop](https://www.amazon.com/Machine-Learning-Workshop-high-performance-scikit-learn/dp/1839219068/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1611061956&sr=1-1&utm_source=github&utm_medium=repository&utm_campaign=9781801070065&utm_term=Machine%20Learning&utm_content=The%20Machine%20Learning%20Workshop) gets you up and running with programming machine learning algorithms. By showing you how to leverage scikit-learn's flexibility, it teaches you all the skills you need to use machine learning to solve real-world problems.

## What you will learn

* Understand how to select an algorithm that best fits your dataset and desired outcome

* Explore popular real-world algorithms such as K-means, Mean-Shift, and DBSCAN

* Discover different approaches to solve machine learning classification problems

* Develop neural network structures using the scikit-learn package

* Use the NN algorithm to create models for predicting future outcomes

* Perform error analysis to improve your model's performance 

## Related Workshops

If you've found this repository useful, you might want to check out some of our other workshop titles:

* [The Supervised Learning Workshop](https://www.amazon.com/Supervised-Learning-Workshop-Interactive-Understanding-dp-1800209045/dp/1800209045/ref=mt_other?_encoding=UTF8&me=&qid=1611062666&utm_source=github&utm_medium=repository&utm_campaign=9781800209046&utm_term=Supervised%20Learning&utm_content=The%20Supervised%20Learning%20Workshop)

* [The Unsupervised Learning Workshop](https://www.amazon.com/Unsupervised-Learning-Workshop-unsupervised-unorganized/dp/1800200706/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1611062803&sr=1-1&utm_source=github&utm_medium=repository&utm_campaign=9781801070515&utm_term=Unsupervised%20Learning&utm_content=The%20Unsupervised%20Learning%20Workshop)

* [The Reinforcement Learning Workshop](https://www.amazon.com/Reinforcement-Learning-Workshop-cutting-edge-reinforcement-dp-1800200455/dp/1800200455/ref=mt_other?_encoding=UTF8&me=&qid=1611062513&utm_source=github&utm_medium=repository&utm_campaign=9781800200456&utm_term=Reinforcement%20Learning&utm_content=The%20Reinforcement%20Learning%20Workshop)