About the course
An overview of machine learning with hands-on implementation of classification models
This course will give you a fundamental understanding of machine learning with a focus on building classification models. The basic concepts of machine learning (ML) are explained, including supervised and unsupervised learning; regression and classification; and overfitting. There are three 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.
Style and Approach
Hands-on course to Introduction to ML Classification Models using scikit-learn
What You Will Learn
- Have a broad understanding of ML and hands-on experience with building classification models using support vector machines, decision trees, and random forests in Python's scikit-learn
Loonycorn is Janani Ravi and Vitthal Srinivasan. Between them, they have studied at Stanford, been admitted to IIM Ahmedabad, and have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore. Janani spent 7 years at Google (New York, Singapore); Studied at Stanford and also worked at Flipkart and Microsoft. Vitthal also worked at Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too. They think they might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why they are so excited to be here. They hope you will try their offerings, and you'll like them.
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