mlcourse.ai is an open and free Machine Learning course, that has been led by OpenDataScience (a.k.a. ods.ai) from spring 2017. This fall, from Sept. 2nd till Nov. 24th, you can join the last session of this course. In a nutshell, the course is focused on practice (you’ll have several Kaggle Inclass competitions and assignments over these 10 weeks) but will also teach you theory needed to understand the techniques that you’ll be heavily using.
Each session we offer something new, and this time we’ll have 4 quizzes and live web-sessions (by Yury Kashnitsky) which will serve as a means of contacting course leaders live, getting feedback and answers to some of your questions.
Roughly sketched syllabus for this session:
Module 1. Exploratory Data Analysis
Module 2. Decision trees, Random Forest, and Gradient boosting
Module 3. Linear classification and regression models
Module 4. Unsupervised learning, online learning, and time series
In each module, you’ll have several articles, a quiz, and an assignment (sometimes in a form of a competition).
All course material is already there:
- Kaggle Dataset with reproducible web-based notebooks: Kaggle Kernels
- Youtube channel with lectures
- Course repository
The course is open for everyone, however, we expect from participants to be familiar with basics of math and Python programming. See the corresponding page with instructions on how to catch up.
How to join
What if I miss this session?
By the end of this session, mlcourse.ai will turn into a self-paced course, which is also good. But passing the course with a couple thousands of other participants is way-way better, so take your chance! Good luck!
—- Originally posted here
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