andriygav/MachineLearningSeminars
Семинары А.В. Грабового к лекционному курсу К.В. Воронцова.
This content provides practical guidance and assignments for students learning machine learning. It covers essential topics like data analysis, preprocessing, model experimentation, and result interpretation. It is designed for students enrolled in machine learning courses, helping them apply theoretical concepts to real-world datasets.
380 stars.
Use this if you are a student taking a machine learning course and need structured seminars and homework to practice data analysis, model building, and result reporting.
Not ideal if you are looking for a plug-and-play machine learning library or a tool for automated model deployment, as this focuses on educational assignments and conceptual understanding.
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380
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160
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 17, 2026
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