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Scikit Learn - User Guide

This project was started in 2007 as a Google Summer of Code project by David Cournapeau. Later that year, Matthieu Brucher started work on this project as part of his thesis. In 2010 Fabian Pedregosa, Gael Varoquaux, Alexandre Gramfort and Vincent Michel of INRIA took leadership of the project and made the first public release, February the 1st 2010. Since then, several releases have appeared following a ~ 3-month cycle, and a thriving international community has been leading the development.

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EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and Information Processing

Subjects:

Computing

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Machine learning Python (Computer program language)

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Machine Learning Explainability

Extract human-understandable insights from any machine learning model.

Subjects:

Computing

Keywords:

Python (Computer program language) Machine learning

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Others
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Intermediate Machine Learning

Learn to handle missing values, non-numeric values, data leakage and more. Your models will be more accurate and useful.

Subjects:

Computing

Keywords:

Python (Computer program language) Machine learning

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Others
Others

Deep Learning

Use TensorFlow to take machine learning to the next level. Your new skills will amaze you.

Subjects:

Computing

Keywords:

Python (Computer program language) Machine learning

Resource Type:

Others
Others

Feature Engineering

Discover the most effective way to improve your models.

Subjects:

Computing

Keywords:

Machine learning Data mining Python (Computer program language)

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Scikit Learn - User Guide

Machine Learning Explainability

Intermediate Machine Learning

Deep Learning

Feature Engineering

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