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  • Language
    Jupyter Notebook
  • License
    MIT License
  • Created over 4 years ago
  • Updated about 1 year ago

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Repository Details

Projects and awesome list for all Data Science fields

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  • For Deep Learning algorithms please check Deep Learning repository.

💠 Data Science Tasks

Folders with all materials for specific task/domain

👩🏻‍🏫 Educational Platforms

🎓 University Courses

Title Description
MIT OpenCourseWare

Julia language

Title Description
Introduction to Computational Thinking

🔢 Time Series

Title Description
MIT 18.S096 Topics in Mathematics w Applications in Finance

    The purpose of the class is to expose undergraduate and graduate students to the mathematical concepts and techniques used in the financial industry. Mathematics lectures are mixed with lectures illustrating the corresponding application in the financial industry. MIT mathematicians teach the mathematics part while industry professionals give the lectures on applications in finance.

  • Video lectures

👩🏻‍🏫 Online Courses

:octocat: GitHub Repositories

Title Description
Data Science for Beginners - A Curriculum Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.
Machine Learning for Beginners - A Curriculum Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 26-lesson curriculum all about Machine Learning. In this curriculum, you will learn about what is sometimes called classic machine learning, using primarily Scikit-learn as a library and avoiding deep learning, which is covered in our forthcoming 'AI for Beginners' curriculum.
start-machine-learning A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques
Data Science Specialization, John Hopkins Coursera Data Science Repo and blog for John Hopkins Coursera Courses. Blog post - Blogging through the Data Science Specialization, John Hopkins Coursera

📚 Books

:octocat: GitHub Repositories

Title Description
Awesome Artificial Intelligence (AI) A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
ml-surveys Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
awesome-analytics-engineering Awesome list of resources for analytics engineers.
Complete-Life-Cycle-of-a-Data-Science-Project
Data Science Learning Path A complete guide to learn data science for beginners
Project Based Learning A list of programming tutorials in which aspiring software developers learn how to build an application from scratch. These tutorials are divided into different primary programming languages. Tutorials may involve multiple technologies and languages.

⚙️ Tools

Title Description

📄 Papers

Title Description, Information
2021: A Year Full of Amazing AI papers- A Review / 📌 [work in progress...] A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code. [work in progress]

📜 Certifications

🗣️ Online Conferences, Meetups, Data Summer Schools

🐦 Twitter

🎧 Podcasts

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📰 Articles

🫂 Communities

Title Description
Coursera Comminity Data Science
Locally Optimistic A community for current and aspiring data analytics leaders. Started in NYC in early 2018 as an outgrowth of a slack channel / extremely informal meetup group, we hope to share our thoughts / opinions / experiences / trials / tribulations with others in the community.
Deepchecks Community A place to talk about MLOps news, articles, conferences, and really just anything in the MLOps space.

🔹 Telegram Chanels

  • DataScience Digest
    • Collection of the top articles, videos, events, books and jobs on Machine Learning, Deep Learning, NLP, Computer Vision and other aspects of Data Science.