rasbt/pydata-chicago2016-ml-tutorial
Machine learning with scikit-learn tutorial at PyData Chicago 2016
This tutorial introduces Python developers to machine learning using the scikit-learn library. It takes raw, labeled datasets and guides you through building powerful classification and regression models. This is for Python developers who want to learn how to apply predictive modeling in their applications.
128 stars. No commits in the last 6 months.
Use this if you are a Python developer new to machine learning and want a hands-on introduction to scikit-learn.
Not ideal if you are an experienced machine learning practitioner or are looking for advanced topics beyond an introduction.
Stars
128
Forks
109
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 18, 2016
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rasbt/pydata-chicago2016-ml-tutorial"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
microsoft/ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
jzsmoreno/likelihood
Code generated from the Machine Learning course to optimization tasks
john-science/scipy_con_2019
Tutorial Sessions for SciPy Con 2019
ethen8181/machine-learning
:earth_americas: machine learning tutorials (mainly in Python3)
x4nth055/pythoncode-tutorials
The Python Code Tutorials