mlcourse.ai is an open Machine Learning course by OpenDataScience, lead by Yury Kashnitsky (yorko). The course is designed to perfectly balance theory and practice. You can take part in several Kaggle Inclass competitions held during the course. From spring 2017 to fall 2019, 6 sessions of mlcourse.ai took place – 26k participants applied, 10k converted to passing the first assignment, about 1500 participants finished the course. Currently, the course is in a self-paced mode. Check out a thorough Roadmap guiding you through the self-paced mlcourse.ai.
The course aims at a perfect balance between theory and practice. Therefore, prerequisites include:
- Python
- Math
- Software requirements
- DevOps
Course consists of 9 Practice Assignments and Kaggle Capstone Project:
- Exploratory data analysis with Pandas
- Analyzing cardiovascular disease data
- Decision trees with a toy task and the UCI Adult dataset
- Sarcasm detection, Kaggle Kernel, solution. Linear Regression as an optimization problem
- Logistic Regression and Random Forest in the credit scoring problem
- Exploring OLS, Lasso and Random Forest in a regression task
- Unsupervised learning
- Implementing online regressor
- Time series analysis