Open Machine Learning Course
Outline
These are the topics of Medium articles to appear from Feb 5 to Apr 7, 2018 (every Monday). The articles (Medium "stories" in a "Publication") will be in English
- Exploratory data analysis with Pandas
🇷🇺 - Visual data analysis with Python
🇷🇺 - Classification, decision trees and k Nearest Neighbors
🇷🇺 - Linear classification and regression
🇷🇺 - Bagging and random forest
🇷🇺 - Feature engineering and feature selection
🇷🇺 - Unsupervised learning: Principal Component Analysis and clustering
🇷🇺 - Vowpal Wabbit: learning with gigabytes of data
🇷🇺 🇬🇧 - Time series analysis with Python
🇷🇺 - Gradient boosting
🇷🇺
Assignments
- "Exploratory data analysis with Pandas", ipynb. Deadline: Feb. 11, 23.59 CET
Community
The discussions between students are held in the #eng_mlcourse_open channel of the OpenDataScience Slack team. Fill in this form to get an invitation. The form will also ask you some personal questions, don't hesitate
Wiki Pages
- Prerequisites: Python, math and DevOps – how to get prepared for the course
- Software requirements and Docker container – this will guide you through installing all necessary stuff for working with course materials