texnar1511/intro_ml_2022

2022 Introduction to Machine Learning and Data Analysis

This is a repo for a 2022 course at the Department of Cosmic Research, MSU. The course covers the very basic concepts of ML, it is obligatory for 4th year students, and for MS students it is an elective course.

General info

• The course consists of 12 lectures and 12 seminars and 5 homeworks.
• All lectures and seminars will be held online via Zoom and probably recorded (Zoom screen capture).
• PDFs with lecture slides will be published here: https://disk.yandex.ru/d/ftlAXAWOxYqxnw
• All homeworks are to be submitted online.

!!There will be no exams, final mark is based on homeworks only!!

Communication

• email [email protected]
• telegram news channel: https://t.me/+mlstxc99aQM2NWEy
• telegram chat room: https://t.me/+g5h-t9Q20K04NDZi

Lectures and seminars

The timetable may be change.

• Lectures: 09:00 - 10:20 (UTC+3, Europe/Moscow)
• Seminars: 10:40 - 12:00 (UTC+3, Europe/Moscow)

Presentations and videos can be downloaded from here: https://disk.yandex.ru/d/ftlAXAWOxYqxnw

#	Date	Lecture	Seminar	Homework
1	2022-09-09	Introduction to the topic	How to manage this course	HW#1
2	2022-09-16	Metric Algorithms, kNN	Classification Quality Metrics	-
3	2022-09-23	Decision Trees	How to tune hyperparameters	-
4	2022-09-30	Linear Models	Invited speaker: Intro to Data Visualization	HW#2
5	2022-10-07	SVM	PCA and SVD	-
6	2022-10-14	Regularized Linear Models	Invited Speaker: A/B Tests and Metrics	HW#3
7	2022-10-21	Time Series	Practical Analytics: when to alert	-
8	2022-10-28	Text Classification	Practical Analytics: SQL	HW#4
9	2022-11-11	Bayes approach, EM	Practical Analytics	-
10	2022-11-18	Clustering	Invited Speaker: Seismic Fault Detection	HW#5
11	2022-11-25	Ranking	TBA	-
12	2022-12-02	Gradient Boosting	TBA	-
13	2022-12-09	No Lecture Here	TBA	-

Homeworks and deadlines

• Each homework has its deadline. Submission after deadline will reduce points
• Submission after the deadline: each score is multiplied by 0.5

#	Name	Date Published	Deadline	Link
1	HW#1	2022-09-09	2022-10-06 23:00:00 +03:00	https://github.com/cosmic-research-ml-edu/intro_ml_2022/blob/main/homeworks/hw01/lab01.ipynb
2	HW#2	2022-09-30	2022-10-20 23:00:00 +03:00	https://github.com/cosmic-research-ml-edu/intro_ml_2022/blob/main/homeworks/hw02/lab02.ipynb
3	HW#3	2022-10-14	2022-11-03 23:00:00 +03:00	https://github.com/cosmic-research-ml-edu/intro_ml_2022/blob/main/homeworks/hw03/lab03.ipynb
4	HW#4	2022-10-28	2022-10-28 23:00:00 +03:00
5	HW#5	2022-11-18	2022-11-18 23:00:00 +03:00

Acknowledgements

This course was inspired by

• The course by Konstantin Vorontsov from the Coursera [link]
• MIT OpenCourseWare Machine Learning course: Rohit Singh, Tommi Jaakkola, and Ali Mohammad. 6.867 Machine Learning. Fall 2006. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.
• Data Mining In Action: [link]
• Author's personal experience in Data Science obtained from Yandex School of Data Science [link], working at Yandex [link], Lensa [link] and various ML-projects.