Stars
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
A complete computer science study plan to become a software engineer.
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
Course on recommender systems conducted at the Faculty of Computer Science, National Research University - Higher School of Economics. Academic year 2022-2023.
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Source code accompanying O'Reilly book: Machine Learning Design Patterns
A curated list of awesome Machine Learning frameworks, libraries and software.
Data science interview questions and answers
Answers to 120 commonly asked data science interview questions.
Data science interview questions with answers. Not ideally (yet)
Quantitative Interview Preparation Guide, updated version here ==>
YSDA course in Natural Language Processing
A course in reinforcement learning in the wild
DL course co-developed by YSDA, HSE and Skoltech
Машинное обучение на ФКН ВШЭ
Free MLOps course from DataTalks.Club
My small cheatsheets for data science, ML, computer science and more.
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering