Roadmap

All activities accounted for in fall 2019 rating.

Plan

  • Calendar and deadlines
  • Assignments
  • Quizzes & Live sessions
  • Kaggle Inclass Competition “DOTA 2 winner prediction”

Calendar and deadlines

Google Calendar with all deadlines.

Current deadlines (see also the assignments page):

  • September 15 - A1
  • September 27 - Quiz1
  • October 6 - A2
  • October 18 - Quiz2
  • October 27 - A3
  • November 8 - Quiz3
  • November 17 - A4 & A5
  • November 18 - DotA submissions
  • November 20 - DotA solutions

All deadlines are 20:59 CET (London time).

Assignments

Assignments are announced in the #mlcourse_ai_news channel in ODS Slack team (pinned items). Also, links to fresh assignments are provided in the Readme file of the course repository and on mlcourse.ai/assignments. Deadlines are typically on Sundays, 20:59 CET. Apart from that, you can practice with demo assignments, don’t confuse them with “real” ones. Rough plan for fall 2019 assignments is the following:

  • A1. Pandas and data analysis
  • A2. Decision trees, random forest, and gradient boosting. Beating a baseline in a competition (gradient boosting)
  • A3. Beating baselines in a competition (linear models)
  • A4. Beating baselines in one more competition using Vowpal Wabbit
  • A5. Time series analysis with Python

If stuck with assignments, check course video lectures.

Quizzes & Live sessions

Quizzes are intended to check your understanding of theory behind the applied approaches. Will be announced in the #mlcourse_ai_news channel as well.

  • Q1. Decision trees, random forest, and gradient boosting. From Sept 9 to Sept 27
  • Q2. Linear models. From Oct 7 to Oct 18
  • Q3. Time series, unsupervised learning. From Oct 28 to Nov 8

Deadline for each quiz is Friday, each quiz is followed by a live session on 3 Saturday mornings. During live session we go through quiz questions and have agile debates.

Kaggle Inclass Competition “DotA 2 winner prediction”

In this competition you are going to utilize all knowledge and skills acquired during the course session. Discussions are held on Kaggle itself, here is an introductory thread.

Rules:

  • Deadline for submissions: 2019 November 18, 20:59 CET
  • Teams up to 4 people are allowed.
  • Instructions on team naming and uploading your solutions will be given (similar to this post on Kaggle)
  • The results of the competition and the final course rating will be published on 2019 November 22.

Credits

Grading is as close as possible to “real” Kaggle competitions, each team member gets the specified amount of credits

  • 1 place – 60 credits
  • 2 place – 50 credits
  • 3 place – 40 credits
  • 4-10 place – 30 credits
  • top 10% - 20 credits
  • top 20% - 10 credits

to be extended.