Projects and awesome list for all Data Science fields
408
stars
348
commits
Jupyter Notebook
primary language
Nov 7, 2024
updated
awesome
awesome-data-science
awesome-interview-preparation
awesome-list
awesome-lists
awesome-ml
data-analysis
data-analyst
data-analytics
data-science
data-scientist
interview
interview-preparation-resources
machine-learning
udacity
udemy
README
🔄 Constantly updated. Subscribe not to miss anything.
- For Natural Language Processing (NLU = NLP + NLG) please check Natural Language Processing repository.
- For Machine Learning algorithms please check Machine Learning repository.
- For Deep Learning algorithms please check Deep Learning repository.
- For Computer Vision please check Computer Vision repository.
💠 Data Science Tasks
Folders with all materials for specific task/domain
- AR VR
- Class Imbalance Problem
- Cloud Computing
- Data Analysis
- Data Analytics
- Data Engineering
- Data Preprocessing
- Data Processing
- Data Science Life Cycle Methodologies
- Data Warehouse
- Data-Centric AI
- Data
- Graph Neural Networks
- Machine Learning Ops (MLOps)
- Optimization
- Overfitting
- Pipelines
- SQL
- Statistics
- Tools and Tips
👩🏻🏫 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. |
👩🏻🏫 Online Courses
- Специализация Наука о данных для руководителей
- Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
- DeepLearning.AI
- 📹 DeepLearning.AI YouTube channel
- 📰 DeepLearning.AI
: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
- Python Data Science Handbook
- Hands-On Machine Learning with Scikit-Learn and TensorFlow
- Machine Learning Notebooks
-
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
-
- Machine Learning Notebooks
: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
- :octocat: papers-with-video
| 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
- TensorFlow Developer Certificate
- Certified Analytics Professional (CAP)
- Cloudera Certified Associate: Data Analyst
- Cloudera Certified Professional: CCP Data Engineer
- Data Science Council of America (DASCA) Senior Data Scientist (SDS)
- Data Science Council of America (DASCA) Principal Data Scientist (PDS)
- Dell EMC Data Science Track
- Google Certified Professional Data Engineer
- Google Data and Machine Learning
- IBM Data Science Professional Certificate
- Microsoft MCSE: Data Management and Analytics
- Microsoft Certified Azure Data Scientist Associate
- Open Certified Data Scientist
- SAS Certified Advanced Analytics Professional
- SAS Certified Big Data Professional
- SAS Certified Data Scientist
🗣️ Online Conferences, Meetups, Data Summer Schools
- Live Webinars & On-demand Recordings by ODSC COMMUNITY
- Data Science fwdays'19 (playlist)
- Webinars 2020, Computer Science UCU
- Eastern European Machine Learning Summer School, 2020 (Deep Learning and Reinforcement Learning
- Program
- Practical Sessions 2020, GitHub Repository
🎧 Podcasts
- Lex Fridman Podcast | Artificial Intelligence (AI)
- Machine Learning, Andrew Ng, Stanford
- Awesome Data Podcasts
🗞️ Blogs
Companies Blogs
-
- :octocat: Software Engineering Blogs
-
A curated list of engineering blogs
- Amazon | Science
- AWS Machine Learning Blog
- Meta AI
- The Netflix Tech Blog
- Uber Engineering
- NVIDIA Developer
- The Stanford AI Lab Blog
Other Blogs
- Towards AI
- Tutorials
-
AI-related tutorials.
-
- Tutorials
- Data Notes
- Louis Bouchard | @What's AI - Making AI Accessible
- Michael Galarnyk
- Data Science Dojo
- DeepLearning.AI
📰 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.
Contributors
ElizaLo
348 commits
Similar repos
Languages
Jupyter Notebook
100.0%
Projects and awesome list for all Data Science fields
408
stars
348
commits
Jupyter Notebook
primary language
Nov 7, 2024
updated
awesome
awesome-data-science
awesome-interview-preparation
awesome-list
awesome-lists
awesome-ml
data-analysis
data-analyst
data-analytics
data-science
data-scientist
interview
interview-preparation-resources
machine-learning
udacity
udemy
README
🔄 Constantly updated. Subscribe not to miss anything.
- For Natural Language Processing (NLU = NLP + NLG) please check Natural Language Processing repository.
- For Machine Learning algorithms please check Machine Learning repository.
- For Deep Learning algorithms please check Deep Learning repository.
- For Computer Vision please check Computer Vision repository.
💠 Data Science Tasks
Folders with all materials for specific task/domain
- AR VR
- Class Imbalance Problem
- Cloud Computing
- Data Analysis
- Data Analytics
- Data Engineering
- Data Preprocessing
- Data Processing
- Data Science Life Cycle Methodologies
- Data Warehouse
- Data-Centric AI
- Data
- Graph Neural Networks
- Machine Learning Ops (MLOps)
- Optimization
- Overfitting
- Pipelines
- SQL
- Statistics
- Tools and Tips
👩🏻🏫 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. |
👩🏻🏫 Online Courses
- Специализация Наука о данных для руководителей
- Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
- DeepLearning.AI
- 📹 DeepLearning.AI YouTube channel
- 📰 DeepLearning.AI
: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
- Python Data Science Handbook
- Hands-On Machine Learning with Scikit-Learn and TensorFlow
- Machine Learning Notebooks
-
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
-
- Machine Learning Notebooks
: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
- :octocat: papers-with-video
| 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
- TensorFlow Developer Certificate
- Certified Analytics Professional (CAP)
- Cloudera Certified Associate: Data Analyst
- Cloudera Certified Professional: CCP Data Engineer
- Data Science Council of America (DASCA) Senior Data Scientist (SDS)
- Data Science Council of America (DASCA) Principal Data Scientist (PDS)
- Dell EMC Data Science Track
- Google Certified Professional Data Engineer
- Google Data and Machine Learning
- IBM Data Science Professional Certificate
- Microsoft MCSE: Data Management and Analytics
- Microsoft Certified Azure Data Scientist Associate
- Open Certified Data Scientist
- SAS Certified Advanced Analytics Professional
- SAS Certified Big Data Professional
- SAS Certified Data Scientist
🗣️ Online Conferences, Meetups, Data Summer Schools
- Live Webinars & On-demand Recordings by ODSC COMMUNITY
- Data Science fwdays'19 (playlist)
- Webinars 2020, Computer Science UCU
- Eastern European Machine Learning Summer School, 2020 (Deep Learning and Reinforcement Learning
- Program
- Practical Sessions 2020, GitHub Repository
🎧 Podcasts
- Lex Fridman Podcast | Artificial Intelligence (AI)
- Machine Learning, Andrew Ng, Stanford
- Awesome Data Podcasts
🗞️ Blogs
Companies Blogs
-
- :octocat: Software Engineering Blogs
-
A curated list of engineering blogs
- Amazon | Science
- AWS Machine Learning Blog
- Meta AI
- The Netflix Tech Blog
- Uber Engineering
- NVIDIA Developer
- The Stanford AI Lab Blog
Other Blogs
- Towards AI
- Tutorials
-
AI-related tutorials.
-
- Tutorials
- Data Notes
- Louis Bouchard | @What's AI - Making AI Accessible
- Michael Galarnyk
- Data Science Dojo
- DeepLearning.AI
📰 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.
Similar repos
Contributors
ElizaLo
348 commits
Languages
Jupyter Notebook
100.0%