An Easy Introduction to Machine Learning Using scikit-learn

An overview of Machine Learning with hands-on implementation of classification models using Python's scikit-learn

What's Inside

This course will give you a fundamental understanding of Machine Learning overall with a focus on building classification models. Basic ML concepts of ML are explained, including Supervised and Unsupervised Learning; Regression and Classification; and Overfitting. There are 3 lab sections which focus on building classification models using Support Vector Machines, Decision Trees and Random Forests using real data sets. The implementation will be performed using the scikit-learn library for Python.

The Intro to ML Classification Models course is meant for developers or data scientists (or anybody else) who knows basic Python programming and wishes to learn about Machine Learning, with a focus on solving the problem of classification.

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5345+ Students
18 Lectures
0+ Hours of Video
Lifetime Access
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Loonycorn

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertises at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

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