An overview of Machine Learning with hands-on implementation of classification models using Python's scikit-learn
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.
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
3 Lectures
3 Lectures
5 Lectures
2 Lectures
Loonycorn is us, Janani Ravi and Vitthal Srinivasan. Between us, we 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: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft Vitthal: Also Google (Singapore) and studied at...
formulas and mathematical explanation can be added
Very clear distinction on explaining and that's important !
Nice mini-course on scikit and decision tree/random forest classifiers -- very good for building confidence in using Python ML packages, I think.
Instructor gave good examples, really condensed everything well. Just wanted more examples and more working examples to copy paste into my own jupyter books.
The instructor is great! Very well organized, very clear explanations, and very clear coding examples! I like that fact that both the explanations and the examples are short and to the point. Great course! Thanks!
Very nice tutorial to have insights about scikit and a great starting point to investigate further. What I was looking for, cheers!
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Hadi E.
Was a good course that covers theory and practice. Would have liked to see more use-cases of the ensemble training.