🇷🇺 Russian version 🇷🇺
❗ 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 ❗
This is the list of published articles on medium.com 🇬🇧, habr.com 🇷🇺, and jqr.com 🇨🇳. Icons are clickable. Also, links to Kaggle Kernels (in English) are given. This way one can reproduce everything without installing a single package.
- Exploratory Data Analysis with Pandas 🇬🇧 🇷🇺 🇨🇳, Kaggle Kernel
- Visual Data Analysis with Python 🇬🇧 🇷🇺 🇨🇳, Kaggle Kernels: part1, part2
- Classification, Decision Trees and k Nearest Neighbors 🇬🇧 🇷🇺 🇨🇳, Kaggle Kernel
- Linear Classification and Regression 🇬🇧 🇷🇺 🇨🇳, Kaggle Kernels: part1, part2, part3, part4, part5
- Bagging and Random Forest 🇬🇧 🇷🇺 🇨🇳, Kaggle Kernels: part1, part2, part3
- Feature Engineering and Feature Selection 🇬🇧 🇷🇺 🇨🇳, Kaggle Kernel
- Unsupervised Learning: Principal Component Analysis and Clustering 🇬🇧 🇷🇺, Kaggle Kernel
- Vowpal Wabbit: Learning with Gigabytes of Data 🇬🇧 🇷🇺, Kaggle Kernel
- Time Series Analysis with Python, part 1 🇬🇧 🇷🇺. Predicting future with Facebook Prophet, part 2 🇬🇧, Kaggle Kernels: part1, part2
- Gradient Boosting 🇬🇧 🇷🇺, Kaggle Kernel
In a new run of the course, assignments will be announced each week. Meanwhile, you can pratice with demo versions. Solutions will be shared in the end of July, 2018.
- Exploratory data analysis with Pandas, nbviewer, Kaggle Kernel
- Analyzing cardiovascular disease data, nbviewer, Kaggle Kernel
- Decision trees with a toy task and the UCI Adult dataset, nbviewer, Kaggle Kernel
- Linear Regression as an optimization problem, nbviewer, Kaggle Kernel
- Logistic Regression and Random Forest in the credit scoring problem, nbviewer, Kaggle Kernel
- Exploring OLS, Lasso and Random Forest in a regression task, nbviewer, Kaggle Kernel
- Unupervised learning, nbviewer, Kaggle Kernel
- Implementing online regressor, nbviewer, Kaggle Kernel
- Time series analysis, nbviewer, Kaggle Kernel
- Gradient boosting and flight delays, nbviewer, Kaggle Kernel
- Catch Me If You Can: Intruder Detection through Webpage Session Tracking. Kaggle Inclass
- How good is your Medium article? Kaggle Inclass
The course is also available in a form of a Kaggle Dataset.
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 👋
- 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
- 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