Machine Learning Open Source University is an IDEA of free-learning of a ML enthusiast for all other ML enthusiast

This list is continuously updated - And if you are a Ml practitioner and have some good suggestions to improve this or have somegood resources to share, you create pull request and contribute.

Table of Contents

1. Getting Started
2. Mathematics
3. Machine Learning
4. Deep Learning
5. Natural language processing
6. Reinforcement learning
7. Books
8. ML in Production
9. Quantum ML
10. DataSets
11. Other Useful Websites
12. Other Useful GitRrpo
13. Blogs and Webinar
14. Must Read Paper Survey/Research

1. Papers with Code
2. Two Minute Papers - Youtube
3. The Missing Semester of Your CS Education
4. Workera : Measure data-AI skills
5. Machine learning mastery
6. From Data to viz: Guide for your graph
7. datatalks club
8. Machine Learning for Art
9. applyingml
10. Deep Learning Drizzle
11. The Machine & Deep Learning Compendium
12. connectedpapers - Research Papers

1. Applied-ml - Papers and blogs by organizations
2. List Machine learning Python libraries
3. ML From Scratch - Implementations of models/algorithms
4. What the f*ck Python?
5. scikit-learn user guide: step-step approach
6. NLP Tutorial Code with DL
7. awesome-mlops
8. Text Classification Algorithms: A Survey
9. ML use cases by company

1. Recommendation algorithms and System design
2. Machine Learning System Design
3. Lil'BLog

NLP [Text]

1. Text Classification Algorithms: A Survey
2. Deep Learning Based Text Classification: A Comprehensive Review
3. Compression of Deep Learning Models for Text: A Survey
4. A Survey on Text Classification: From Shallow to Deep Learning
5. A Survey of Transformers
6. AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing
7. Graph Neural Networks for Natural Language Processing: A Survey
8. A Survey of Data Augmentation Approaches for NLP
9. A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios
10. Evaluation of Text Generation: A Survey
11. A Survey of Transfer learning In NLP