Modules / Lectures

Sl.No Chapter Name English
1Probability part 1PDF unavailable
2Probability part 2PDF unavailable
3Probability part 3PDF unavailable
4Math Foundation part 1PDF unavailable
5Math Foundation part 2PDF unavailable
6Math Foundation part 3PDF unavailable
7Math Foundation 2 part 1PDF unavailable
8Math Foundation 2 part 2PDF unavailable
9Math Foundation 2 part 3PDF unavailable
10Introduction to probability for Data science part 1PDF unavailable
11Introduction to probability for Data science part 2PDF unavailable
12Introduction to probability for Data science part 3PDF unavailable
13Introduction to Statistics for Data science part 1PDF unavailable
14Introduction to Statistics for Data science part 2PDF unavailable
15Introduction to Statistics for Data science part 3PDF unavailable
16Clustering - I part 1PDF unavailable
17Clustering - I part 2PDF unavailable
18Clustering - I part 3PDF unavailable
19Clustering - II part 1PDF unavailable
20Clustering - II part 2PDF unavailable
21Clustering - II part 3PDF unavailable
22Dimensionality Reduction part 1PDF unavailable
23Dimensionality Reduction part 2PDF unavailable
24Dimensionality Reduction part 3PDF unavailable
25Supervised Learning - I part1PDF unavailable
26Supervised Learning - I part 2PDF unavailable
27Supervised Learning - I part 3PDF unavailable
28Supervised Learning - II part 1PDF unavailable
29Supervised Learning - II part 2PDF unavailable
30Supervised Learning - II part 3PDF unavailable
31Supervised Learning - III part 1PDF unavailable
32Supervised Learning - III part 2PDF unavailable
33Supervised Learning - III part 3PDF unavailable
34Linear Models For Classification part 1PDF unavailable
35Linear Models For Classification part 2PDF unavailable
36Linear Models For Classification part 3PDF unavailable
37Tree Based Methods part 1PDF unavailable
38Tree Based Methods part 2PDF unavailable
39SVMs part 1PDF unavailable
40SVMs part 2PDF unavailable
41SVMs part 3PDF unavailable
42Ensemble Methods part 1PDF unavailable
43Ensemble Methods part 2PDF unavailable
44Ensemble Methods part 2PDF unavailable
45Learning Theory part 1PDF unavailable
46Learning Theory part 2PDF unavailable
47Introduction to Probabilistic Modeling part 1PDF unavailable
48Introduction to Probabilistic Modeling part 2PDF unavailable
49Introduction to Probabilistic Modeling part 3PDF unavailable
50Probabilistic / Bayesian Models for Regression part 1PDF unavailable
51Probabilistic / Bayesian Models for Regression part 2PDF unavailable
52Probabilistic / Bayesian Models for Regression part 3PDF unavailable
53Probabilistic Classification, Latent Variable Models part 1PDF unavailable
54Probabilistic Classification, Latent Variable Models part 2PDF unavailable
55Probabilistic Classification, Latent Variable Models part 3PDF unavailable
56Deep Learning - I part 1PDF unavailable
57Deep Learning - I part 2PDF unavailable
58Deep Learning - I part 3PDF unavailable
59Deep Learning - II part 1PDF unavailable
60Deep Learning - II part 2PDF unavailable
61Deep Learning - II part 3PDF unavailable
62Deep Learning - III part 1PDF unavailable
63Deep Learning - III part 2PDF unavailable
64Deep Learning - III part 3PDF unavailable
65Reinforcement learning - I part 1PDF unavailable
66Reinforcement learning - I part 2PDF unavailable
67Reinforcement learning - II part 1PDF unavailable
68Reinforcement learning - II part 2PDF unavailable
69Map - Reduce and Spark par 2PDF unavailable
70Map - Reduce and Spark par 1PDF unavailable
71Map - Reduce and Spark par 3PDF unavailable
72Scalable Machine Learning part 1PDF unavailable
73Scalable Machine Learning part 2PDF unavailable


Sl.No Language Book link
1EnglishNot Available
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available