π·πΊ Russian version π·πΊ
β The next session launches on October 1, 2018. Fill in this form to participate. In September, you'll get an invitation to OpenDataScience Slack team β
This is the list of published articles on Medium π¬π§, Habr.com π·πΊ, and jqr.com π¨π³. Icons are clickable.
- Exploratory Data Analysis with Pandas π¬π§ π·πΊ π¨π³
- Visual Data Analysis with Python π¬π§ π·πΊ π¨π³
- Classification, Decision Trees and k Nearest Neighbors π¬π§ π·πΊ π¨π³
- Linear Classification and Regression π¬π§ π·πΊ π¨π³
- Bagging and Random Forest π¬π§ π·πΊ π¨π³
- Feature Engineering and Feature Selection π¬π§ π·πΊ π¨π³
- Unsupervised Learning: Principal Component Analysis and Clustering π¬π§ π·πΊ
- Vowpal Wabbit: Learning with Gigabytes of Data π¬π§ π·πΊ Kaggle Kernel
- Time Series Analysis with Python, part 1 π¬π§ π·πΊ. Predicting future with Facebook Prophet, part 2 π¬π§
- Gradient Boosting π¬π§ π·πΊ
Each topic is followed by an assignment. Examples are to appear in the end of June, 2018.
- Catch Me If You Can: Intruder Detection through Webpage Session Tracking. Kaggle Inclass
- How good is your Medium article? Kaggle Inclass
Throughout the course we are maintaining a student rating. It takes into account credits scored in assignments and Kaggle competitions. Top students (according to the final rating) will be listed on a special Wiki page.
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 π
- Prerequisites: Python, math and DevOps β how to get prepared for the course
- Software requirements and Docker container β this will guide you through installing all necessary stuff for working with course materials
- 1st session in English: all activities accounted for in rating
The course is free but you can support organizers by making a pledge on Patreon