# Machine Learning (Ml) In Hindi - Institution: IIIT Delhi - Department: Computer Science and Engineering - Teacher: Prof. Anubha Gupta - Level: Undergraduate - Language: English - Subjects: Computer science, Engineering - Source: [NPTEL](https://nptel.ac.in/courses/106106247) - Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.) - Syllabus: [at the source](https://nptel.ac.in/courses/106106247) - Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words) This is an introductory course on Machine Learning (ML) that is offered to undergraduate and graduate students. The contents are designed to cover both theoretical and practical aspects of several well-established ML techniques. The assignments will contain theory and programming questions that help strengthen the theoretical foundations as well as learn how to engineer ML solutions to work on simulated and publicly available real datasets. The project(s) will require students to develop a complete Machine Learning solution requiring preprocessing, design of the classifier/regressor, training and validation, testing, and evaluation with quantitative performance comparisons. Each week’s theory contents will be accompanied with a tutorial on python. Intended audience: Senior UG and PG Students Prerequisites: Mandatory Prerequisites:1. Programming (Python)2.Matrix calculus3.Probability Theory Desirable Prerequisites:1. Linear Algebra ## Lectures 1. [Introduction to Machine Learning](https://invisiblenetwork.ai/learn/nptel/106106247/4cdf94844363) (YouTube) 2. [Linear Algebra: Review (Vector Spaces)](https://invisiblenetwork.ai/learn/nptel/106106247/75b4b50f360c) (YouTube) 3. [Linear Algebra: Review (Matrices)](https://invisiblenetwork.ai/learn/nptel/106106247/782677bd14ef) (YouTube) 4. [Probability Theory: Review (Basics of Probability)](https://invisiblenetwork.ai/learn/nptel/106106247/21e4378795f9) (YouTube) 5. [Probability Theory: Review (Random Variables)](https://invisiblenetwork.ai/learn/nptel/106106247/874e9cd484ae) (YouTube) 6. [Linear Regression](https://invisiblenetwork.ai/learn/nptel/106106247/feee88824018) (YouTube) 7. [Linear Regression](https://invisiblenetwork.ai/learn/nptel/106106247/dd770b3e56b9) (YouTube) 8. [Tutorial: Linear Regression](https://invisiblenetwork.ai/learn/nptel/106106247/998e000908d6) (YouTube) 9. [Linear Regression](https://invisiblenetwork.ai/learn/nptel/106106247/8845688abeb5) (YouTube) 10. [Linear Kernel Regression](https://invisiblenetwork.ai/learn/nptel/106106247/255f3118ef56) (YouTube) 11. [k-Nearest Neighbour (k-NN) Regression](https://invisiblenetwork.ai/learn/nptel/106106247/debcbf691638) (YouTube) 12. [Tutorial: k-NN Regression](https://invisiblenetwork.ai/learn/nptel/106106247/435991dbb41e) (YouTube) 13. [Tutorial: Kernel Regression](https://invisiblenetwork.ai/learn/nptel/106106247/16121563688f) (YouTube) 14. [Logistic Regression: Classification Evaluation Metrics](https://invisiblenetwork.ai/learn/nptel/106106247/9e8a11c86f58) (YouTube) 15. [Logistic Regression](https://invisiblenetwork.ai/learn/nptel/106106247/608433686787) (YouTube) 16. [Logistic Regression: Examples](https://invisiblenetwork.ai/learn/nptel/106106247/1b5f2427eef5) (YouTube) 17. [Tutorial: Logistic Regression](https://invisiblenetwork.ai/learn/nptel/106106247/830cb4af1174) (YouTube) 18. [Neural Networks](https://invisiblenetwork.ai/learn/nptel/106106247/630eea1d0bf2) (YouTube) 19. [Neural Networks](https://invisiblenetwork.ai/learn/nptel/106106247/d62c8684a458) (YouTube) 20. [Neural Networks: Examples](https://invisiblenetwork.ai/learn/nptel/106106247/2fd35fdeee3f) (YouTube) 21. [Tutorial: Neural Networks](https://invisiblenetwork.ai/learn/nptel/106106247/20915c8d86df) (YouTube) 22. [Practical Machine Learning](https://invisiblenetwork.ai/learn/nptel/106106247/9b8f4a018794) (YouTube) 23. [Practical Machine Learning - Part 2](https://invisiblenetwork.ai/learn/nptel/106106247/88dbb6abf126) (YouTube) 24. [Practical Machine Learning - Part 3](https://invisiblenetwork.ai/learn/nptel/106106247/6bccebc60dcc) (YouTube) 25. [Practical Machine Learning - Part 4](https://invisiblenetwork.ai/learn/nptel/106106247/9a1143777025) (YouTube) 26. [Support Vector Machines (SVM)](https://invisiblenetwork.ai/learn/nptel/106106247/f0ef794683b6) (YouTube) 27. [Tutorial: Support Vector Machines (SVM)](https://invisiblenetwork.ai/learn/nptel/106106247/6abec5ad4717) (YouTube) 28. [Kernel Support Vector Machines (k-SVM)](https://invisiblenetwork.ai/learn/nptel/106106247/f38413f2da32) (YouTube) 29. [Naïve Bayes Classification](https://invisiblenetwork.ai/learn/nptel/106106247/a1be7de2ccdc) (YouTube) 30. [Decision Trees - Part 1](https://invisiblenetwork.ai/learn/nptel/106106247/8383c4adfec2) (YouTube) 31. [Decision Trees - Part 2](https://invisiblenetwork.ai/learn/nptel/106106247/75e97f0a7d82) (YouTube) 32. [Tutorial: Naïve Bayes Classification](https://invisiblenetwork.ai/learn/nptel/106106247/35c7c4781f5e) (YouTube) 33. [Tutorial: Decision Trees](https://invisiblenetwork.ai/learn/nptel/106106247/53835c5be2f6) (YouTube) 34. [k-NN Classifier](https://invisiblenetwork.ai/learn/nptel/106106247/47e93b5b714e) (YouTube) 35. [Ensemble Learning](https://invisiblenetwork.ai/learn/nptel/106106247/930cf903598f) (YouTube) 36. [Random Forests](https://invisiblenetwork.ai/learn/nptel/106106247/5b6ba15c7b0c) (YouTube) 37. [Bagging (Bootstrap AGGregatING)](https://invisiblenetwork.ai/learn/nptel/106106247/710f433ee579) (YouTube) 38. [Tutorial: Random Forests](https://invisiblenetwork.ai/learn/nptel/106106247/f3d87c82f83a) (YouTube) 39. [Tutorial: k-NN Classifier & Bootstrap AGGregatING (Bagging)](https://invisiblenetwork.ai/learn/nptel/106106247/cebba0ed1ea4) (YouTube) 40. [Boosting](https://invisiblenetwork.ai/learn/nptel/106106247/d5aced650081) (YouTube) 41. [Clustering](https://invisiblenetwork.ai/learn/nptel/106106247/d5945baa7c16) (YouTube) 42. [k-means Clustering](https://invisiblenetwork.ai/learn/nptel/106106247/ec03a89697e0) (YouTube) 43. [Tutorial: Boosting](https://invisiblenetwork.ai/learn/nptel/106106247/59ec265f477a) (YouTube) 44. [Spectral Clustering](https://invisiblenetwork.ai/learn/nptel/106106247/1ac38b76a62c) (YouTube) 45. [Mixture of Models (Gaussian Mixture Models-GMM)](https://invisiblenetwork.ai/learn/nptel/106106247/22de3e491d6c) (YouTube) 46. [Dimensionality Reduction: Principal Component Analysis (PCA) & kernel PCA](https://invisiblenetwork.ai/learn/nptel/106106247/885c198f4db0) (YouTube) 47. [Tutorial: k-means and Spectral Clustering](https://invisiblenetwork.ai/learn/nptel/106106247/18384b82ba91) (YouTube) 48. [Tutorial: Principal Component Analysis (PCA) and Gaussian Mixture Models (GMM)](https://invisiblenetwork.ai/learn/nptel/106106247/26f151ae0e02) (YouTube) 49. [Introduction to Deep Learning (DL)](https://invisiblenetwork.ai/learn/nptel/106106247/438bc8d8f7dd) (YouTube) 50. [Convolutional Neural Networks (CNN): Part A](https://invisiblenetwork.ai/learn/nptel/106106247/7210f8a63ccc) (YouTube) 51. [Convolutional Neural Networks (CNN): Part B](https://invisiblenetwork.ai/learn/nptel/106106247/6b4d8245c669) (YouTube) 52. [Autoencoders](https://invisiblenetwork.ai/learn/nptel/106106247/15e169f47264) (YouTube) 53. [Applications of ML in Healthcare Problems: Part 1](https://invisiblenetwork.ai/learn/nptel/106106247/acb66ca12e60) (YouTube) 54. [Applications of ML in Healthcare Problems: Part 2](https://invisiblenetwork.ai/learn/nptel/106106247/e0aa0e1bd6b2) (YouTube) 55. [Tutorial: CNN and Autoencoder](https://invisiblenetwork.ai/learn/nptel/106106247/4cce63f1b94c) (YouTube)