Thursday, September 3, 2026

Machine Learning Related usefull links.

 

1. ๐Ÿง  Machine Learning Fundamentals

2. ๐Ÿ Python for Machine Learning

3. ๐Ÿ“Š Supervised Learning

Important technologies:

  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • Gradient Boosting
  • SVM
  • KNN
  • Naive Bayes

Useful library:

4. ๐Ÿ” Unsupervised Learning

  • www.scikit-learn.org
  • www.h2o.ai
  • www.umap-learn.readthedocs.io
  • www.scipy.org

Topics:

  • K-Means
  • DBSCAN
  • Hierarchical Clustering
  • PCA
  • Dimensionality Reduction
  • Anomaly Detection

5. ๐ŸŒณ Decision Trees / Ensemble Learning

XGBoost, LightGBM, CatBoost aur scikit-learn production ML mein commonly used ecosystem ka important part hain; MLflow bhi in frameworks ke model integrations provide karta hai.

6. ๐Ÿง  Deep Learning

7. ๐Ÿ‘️ Computer Vision

8. ๐Ÿ—ฃ️ NLP — Natural Language Processing

9. ๐Ÿค— Hugging Face

10. ๐Ÿ“ˆ Time Series / Forecasting

11. ๐ŸŽฏ Reinforcement Learning

12. ๐Ÿ—ƒ️ Machine Learning Datasets

13. ๐Ÿ† Kaggle

Kaggle especially useful hai datasets + notebooks + competitions + practical ML projects ke liye.

14. ๐Ÿงช Model Evaluation / Experimentation

15. ๐Ÿš€ MLOps

MLflow ab traditional ML ke saath experiment tracking, model packaging, registry, deployment aur evaluation bhi support karta hai.

16. ☁️ AWS Machine Learning

17. ☁️ Microsoft Azure Machine Learning

18. ☁️ Google Cloud Machine Learning

Google ka current ML learning ecosystem fundamentals se lekar ML engineering, Vertex AI, TensorFlow aur MLOps tak cover karta hai.

19. ๐ŸŽ“ Machine Learning Courses

Google ka Machine Learning Crash Course practical exercises aur interactive visualizations ke saath ML fundamentals sikhata hai.

20. ๐Ÿ“ Mathematics for Machine Learning

Important topics:

  • Linear Algebra
  • Probability
  • Statistics
  • Calculus
  • Optimization
  • Gradient Descent

21. ๐Ÿ”ฌ ML Research / Papers

22. ๐Ÿงฉ AutoML

23. ๐Ÿ”ฅ Popular ML Frameworks / Libraries

24. ๐Ÿญ Production ML / Model Deployment

25. ๐Ÿ’ป ML Development / GitHub

26. ๐Ÿง‘‍๐Ÿ’ผ Machine Learning Jobs / Career

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