# Mathematical Foundations of Machine Learning

- Institution: IISc Bangalore
- Department: Computer Science and Engineering
- Teacher: Prof. Prathosh A P
- Level: Undergraduate
- Language: English
- Subjects: Computer science, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/106108841)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/106108841)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

## Lectures

1. [Overview of Function Approximation](https://invisiblenetwork.ai/learn/nptel/106108841/d13c46cc207d) (Video)
2. [Recap of Probability Theory - 1, Part 1](https://invisiblenetwork.ai/learn/nptel/106108841/e1d04b7ec814) (Video)
3. [Recap of Probability Theory - 1, Part 2](https://invisiblenetwork.ai/learn/nptel/106108841/694b3905b017) (Video)
4. [Recap of Probability Theory - 1, Part 3](https://invisiblenetwork.ai/learn/nptel/106108841/a3d15d6807f6) (Video)
5. [Recap of Probability Theory Part 2](https://invisiblenetwork.ai/learn/nptel/106108841/aaffab92a8ea) (Video)
6. [Understanding a Chest X-Ray as Sample from Distribution](https://invisiblenetwork.ai/learn/nptel/106108841/15bb310da426) (Video)
7. [IID Assumption](https://invisiblenetwork.ai/learn/nptel/106108841/3e0f7b219df7) (Video)
8. [Distribution Estimation](https://invisiblenetwork.ai/learn/nptel/106108841/79c1b6545c1f) (Video)
9. [Density Function](https://invisiblenetwork.ai/learn/nptel/106108841/7d9941308f88) (Video)
10. [Challenge With ML](https://invisiblenetwork.ai/learn/nptel/106108841/ef3ad8d44d76) (Video)
11. [Tutorial 1 : Introduction to Python Basics](https://invisiblenetwork.ai/learn/nptel/106108841/1064f34eef7f) (Video)
12. [Tutorial 2 : Simple Problem solving in Probability Theory](https://invisiblenetwork.ai/learn/nptel/106108841/23b30e6f8795) (Video)
13. [Entropy](https://invisiblenetwork.ai/learn/nptel/106108841/6d74fa2cfa8f) (Video)
14. [Kullback-Leibler (KL) Divergence](https://invisiblenetwork.ai/learn/nptel/106108841/6ec29ef5dadf) (Video)
15. [Minimization of KL Divergence](https://invisiblenetwork.ai/learn/nptel/106108841/3bc93c55be58) (Video)
16. [Example of ML Estimate](https://invisiblenetwork.ai/learn/nptel/106108841/8e24de6bc912) (Video)
17. [Risk Minimization Framework](https://invisiblenetwork.ai/learn/nptel/106108841/1096d978eb11) (Video)
18. [Bayes Classifier](https://invisiblenetwork.ai/learn/nptel/106108841/d9039a82f7b4) (Video)
19. [Tutorial 3 : Risk Minimization Framework](https://invisiblenetwork.ai/learn/nptel/106108841/1a2999ba094a) (Video)
20. [MLE for Gaussian Distribution](https://invisiblenetwork.ai/learn/nptel/106108841/12af97287bd0) (Video)
21. [MLE for Generalized Discrete Random Variable](https://invisiblenetwork.ai/learn/nptel/106108841/772ce41ee7f5) (Video)
22. [Density Estimation for Mixed Distribution](https://invisiblenetwork.ai/learn/nptel/106108841/fa7d01174076) (Video)
23. [Latent Variable Models](https://invisiblenetwork.ai/learn/nptel/106108841/7775bcd4b710) (Video)
24. [MLE for Latent Variable Models](https://invisiblenetwork.ai/learn/nptel/106108841/999466f1e492) (Video)
25. [Expectation Maximization Algorithm](https://invisiblenetwork.ai/learn/nptel/106108841/693931d6a7ed) (Video)
26. [Tutorial 4 : Minmax Classifier](https://invisiblenetwork.ai/learn/nptel/106108841/80fffe4e051b) (Video)
27. [Tutorial 5 : Neyman Pearson Classifier](https://invisiblenetwork.ai/learn/nptel/106108841/0cb35bc8902f) (Video)
28. [Tutorial 6 : Example of NP Classifier, ROC Curve](https://invisiblenetwork.ai/learn/nptel/106108841/93e0d315cb1c) (Video)
29. [Tutorial 7A : MLE for Gaussian Distribution](https://invisiblenetwork.ai/learn/nptel/106108841/b622059d78b6) (Video)
30. [Tutorial 7B : MLE for Generalized Discrete Distribution](https://invisiblenetwork.ai/learn/nptel/106108841/251613d7cbf7) (Video)
31. [Convergence of EM](https://invisiblenetwork.ai/learn/nptel/106108841/01d99fb8d5d0) (Video)
32. [EM for GMMs](https://invisiblenetwork.ai/learn/nptel/106108841/d07a17cd60ab) (Video)
33. [MAP Estimate](https://invisiblenetwork.ai/learn/nptel/106108841/1c28c8c8cbff) (Video)
34. [Parzen Window](https://invisiblenetwork.ai/learn/nptel/106108841/6b77aad6583f) (Video)
35. [Nearest Neighbor Classifier](https://invisiblenetwork.ai/learn/nptel/106108841/7ef7e6c1fd55) (Video)
36. [Tutorial 8 : Computation of EM for GMMs](https://invisiblenetwork.ai/learn/nptel/106108841/545d3fa5d1eb) (Video)
37. [Tutorial 9 : MAP Estimate](https://invisiblenetwork.ai/learn/nptel/106108841/c4a30aa10791) (Video)
38. [Ordinary Least Squares (OLS)](https://invisiblenetwork.ai/learn/nptel/106108841/82af50183207) (Video)
39. [Generalized Least Squares (GLS)](https://invisiblenetwork.ai/learn/nptel/106108841/e1f9d571fc82) (Video)
40. [Linear Models for Classification](https://invisiblenetwork.ai/learn/nptel/106108841/559eb78ce938) (Video)
41. [Bias - Variance Decomposition and Analysis](https://invisiblenetwork.ai/learn/nptel/106108841/96dfa7feff89) (Video)
42. [Bias & Variance in Practice](https://invisiblenetwork.ai/learn/nptel/106108841/68b77348fa8d) (Video)
43. [Tutorial 10 Part A : Numerical Example on Bayes Classifier](https://invisiblenetwork.ai/learn/nptel/106108841/3fb950f30537) (Video)
44. [Tutorial 10 Part B : Numerical Example on MLE and MAP Estimate](https://invisiblenetwork.ai/learn/nptel/106108841/730cfe31aac2) (Video)
45. [Regularization](https://invisiblenetwork.ai/learn/nptel/106108841/888a6b0b94b0) (Video)
46. [Regularized ERM and MAP Estimate](https://invisiblenetwork.ai/learn/nptel/106108841/b0d25ad74d1e) (Video)
47. [Stochastic Gradient Descent as a Regularizer](https://invisiblenetwork.ai/learn/nptel/106108841/56100dbe0eb1) (Video)
48. [Max-Margin Classifier and SVM](https://invisiblenetwork.ai/learn/nptel/106108841/9a7d6f728681) (Video)
49. [SVM Formulation](https://invisiblenetwork.ai/learn/nptel/106108841/9dc7c7d05e7f) (Video)
50. [Dual Function in SVM](https://invisiblenetwork.ai/learn/nptel/106108841/32da701b0034) (Video)
51. [SVM for Non-Linear Seperable Case](https://invisiblenetwork.ai/learn/nptel/106108841/3c858d947d91) (Video)
52. [SVM with Kernel Function](https://invisiblenetwork.ai/learn/nptel/106108841/47d2efa00c23) (Video)
53. [Neural Networks and Universal Approximation Theorem](https://invisiblenetwork.ai/learn/nptel/106108841/d3a19829cbc3) (Video)
54. [ERM on Neural Networks and Error Backpropagation](https://invisiblenetwork.ai/learn/nptel/106108841/82a3b9a1abd6) (Video)
55. [Local Receptive Field and Parameter Sharing](https://invisiblenetwork.ai/learn/nptel/106108841/4eae2a330953) (Video)
56. [Convolutional Neural Networks(CNNs) as Regularized MLP](https://invisiblenetwork.ai/learn/nptel/106108841/b0ad07c741d2) (Video)
57. [Recurrent Neural Networks(RNNs)](https://invisiblenetwork.ai/learn/nptel/106108841/c5ef26eb50c8) (Video)
58. [Back Prapogation in RNNs and Vanishing Gradients Problem](https://invisiblenetwork.ai/learn/nptel/106108841/211862345e87) (Video)
59. [LSTMs and GRUs](https://invisiblenetwork.ai/learn/nptel/106108841/fcc4459eae52) (Video)
60. [Tutorial 11 : Pytorch - Tensors and Data Loaders](https://invisiblenetwork.ai/learn/nptel/106108841/9dc8553559b5) (Video)
61. [Tutorial 12 : Pytorch - Building MLP and Auto Grad](https://invisiblenetwork.ai/learn/nptel/106108841/f3ca53ba49ac) (Video)
62. [Tutorial 13 : Pytorch - Training the Model](https://invisiblenetwork.ai/learn/nptel/106108841/1fd7d35403a4) (Video)
63. [Attention Part1](https://invisiblenetwork.ai/learn/nptel/106108841/65080ed1e08d) (Video)
64. [Attention Part2](https://invisiblenetwork.ai/learn/nptel/106108841/f5319d1fd697) (Video)
65. [Multi-Head Attention and Transformer Architecture](https://invisiblenetwork.ai/learn/nptel/106108841/cc6ed05bbb49) (Video)
66. [Positional Embeddings](https://invisiblenetwork.ai/learn/nptel/106108841/4e87a3a0157a) (Video)
67. [Transfer Learning and Knowledge Distilation](https://invisiblenetwork.ai/learn/nptel/106108841/4af18f07a844) (Video)
68. [SGD, RMS Prop, ADAM : Optimizers](https://invisiblenetwork.ai/learn/nptel/106108841/9c104b2c821f) (Video)
69. [Tutorial 14 Part 1 : CNNs](https://invisiblenetwork.ai/learn/nptel/106108841/49baa81749d9) (Video)
70. [Tutorial 14 Part 2 : Transfer Learning using CNNs](https://invisiblenetwork.ai/learn/nptel/106108841/437fd3846fca) (Video)
71. [Tutorial 15 Part 1 : RNNs, LSTMs and GRUs](https://invisiblenetwork.ai/learn/nptel/106108841/1342691fdbee) (Video)
72. [Tutorial 15 Part 2 : Deep RNNs, LSTMs and GRUs](https://invisiblenetwork.ai/learn/nptel/106108841/775acc3f2c85) (Video)
73. [Decision Trees and Impurity Measures](https://invisiblenetwork.ai/learn/nptel/106108841/c5b5e447ecc7) (Video)
74. [Regression Trees](https://invisiblenetwork.ai/learn/nptel/106108841/da0a5cc8c147) (Video)
75. [Ensemble Methods, Bagging and Boosting](https://invisiblenetwork.ai/learn/nptel/106108841/ee2159058a4b) (Video)
76. [Gradient Boosting Algorithm](https://invisiblenetwork.ai/learn/nptel/106108841/738c62d3f779) (Video)
77. [Ada-Boosting](https://invisiblenetwork.ai/learn/nptel/106108841/670d5f435210) (Video)
78. [Cross Validation](https://invisiblenetwork.ai/learn/nptel/106108841/6d92a92701a7) (Video)
79. [Un-Supervised Learning](https://invisiblenetwork.ai/learn/nptel/106108841/f97eb9aeca3b) (Video)
80. [K-Means Clustering](https://invisiblenetwork.ai/learn/nptel/106108841/5beafe4e71c9) (Video)
81. [PCA - Principal Component Analysis](https://invisiblenetwork.ai/learn/nptel/106108841/e82f4ce43534) (Video)
82. [NCE - Noise Contrastive Estimation](https://invisiblenetwork.ai/learn/nptel/106108841/f4e64f9fba0d) (Video)
83. [NCE, Info-NCE, SimCLR, JEPA](https://invisiblenetwork.ai/learn/nptel/106108841/93daaede067e) (Video)
84. [Introduction to Generative Models](https://invisiblenetwork.ai/learn/nptel/106108841/1c988895758d) (Video)
85. [GAN - Generative Adversarial Networks](https://invisiblenetwork.ai/learn/nptel/106108841/b9c9c243d506) (Video)