| Module Name | Download |
|---|---|
| noc20_cs12_assigment_1 | noc20_cs12_assigment_1 |
| noc20_cs12_assigment_2 | noc20_cs12_assigment_2 |
| noc20_cs12_assigment_3 | noc20_cs12_assigment_3 |
| noc20_cs12_assigment_4 | noc20_cs12_assigment_4 |
| noc20_cs12_assigment_5 | noc20_cs12_assigment_5 |
| noc20_cs12_assigment_6 | noc20_cs12_assigment_6 |
| noc20_cs12_assigment_7 | noc20_cs12_assigment_7 |
| noc20_cs12_assigment_8 | noc20_cs12_assigment_8 |
| noc20_cs12_assigment_9 | noc20_cs12_assigment_9 |
| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Lecture 1 Introduction, Knowledge Discovery Process | Download |
| 2 | Lecture 2 Data Preprocessing - I | Download |
| 3 | Lecture 3 Data Preprocessing - II | Download |
| 4 | Lecture 4 Association Rules | Download |
| 5 | Lecture 5 Apriori algorithm | Download |
| 6 | Lecture 6 : Rule generation | Download |
| 7 | Lecture 7 : Classification | Download |
| 8 | Lecture 8 : Decision Tree - I | Download |
| 9 | Lecture 9 : Decision Tree - II | Download |
| 10 | Lecture 10 : Decision Tree III | Download |
| 11 | Lecture 11 : Decision Tree IV | Download |
| 12 | Lecture 12 : Bayes Classifier I | Download |
| 13 | Lecture 13 : Bayes Classifier II | Download |
| 14 | Lecture 14 : Bayes Classifier III | Download |
| 15 | Lecture 15 : Bayes Classifier IV | Download |
| 16 | Lecture 16 : Bayes Classifier V | Download |
| 17 | Lecture 17 : K Nearest Neighbor I | Download |
| 18 | Lecture 18 : K Nearest Neighbor II | Download |
| 19 | Lecture 19 : | Download |
| 20 | Lecture 20 | Download |
| 21 | Lecture 21 | Download |
| 22 | Lecture 22 : Support Vector Machine I | Download |
| 23 | Lecture 23 : Support Vector Machine II | Download |
| 24 | Lecture 24 : Support Vector Machine III | Download |
| 25 | Lecture 25 : Support Vector Machine IV | Download |
| 26 | Lecture 26 : Support Vector Machine V | Download |
| 27 | Lecture 27: Kernel Machines | Download |
| 28 | Lecture 28: Artificial Neural Networks I | Download |
| 29 | Lecture 29:Artificial Neural Networks II | Download |
| 30 | Lecture 30: Artificial Neural Networks III | Download |
| 31 | Lecture 31: Artificial Neural Networks IV | Download |
| 32 | Lecture 32: Clustering I | Download |
| 33 | Lecture 33: Clustering II | Download |
| 34 | Lecture 34: Clustering III | Download |
| 35 | Lecture 35: Clustering IV | Download |
| 36 | Lecture 36: Clustering V | Download |
| 37 | Lecture 37 : Regression I | Download |
| 38 | Lecture 38 : Regression II | Download |
| 39 | Lecture 39 : Regression III | Download |
| 40 | Lecture 40 : Regression IV | Download |
| 41 | Lecture 41 : Dimensionality Reduction - I | Download |
| 42 | Lecture 42 : Dimensionality Reduction - II | Download |
| 43 | Lecture 43 : Tutorial | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Lecture 1 Introduction, Knowledge Discovery Process | Download To be verified |
| 2 | Lecture 2 Data Preprocessing - I | Download To be verified |
| 3 | Lecture 3 Data Preprocessing - II | Download To be verified |
| 4 | Lecture 4 Association Rules | Download To be verified |
| 5 | Lecture 5 Apriori algorithm | Download To be verified |
| 6 | Lecture 6 : Rule generation | Download To be verified |
| 7 | Lecture 7 : Classification | Download To be verified |
| 8 | Lecture 8 : Decision Tree - I | Download To be verified |
| 9 | Lecture 9 : Decision Tree - II | Download To be verified |
| 10 | Lecture 10 : Decision Tree III | Download To be verified |
| 11 | Lecture 11 : Decision Tree IV | Download To be verified |
| 12 | Lecture 12 : Bayes Classifier I | Download To be verified |
| 13 | Lecture 13 : Bayes Classifier II | Download To be verified |
| 14 | Lecture 14 : Bayes Classifier III | Download To be verified |
| 15 | Lecture 15 : Bayes Classifier IV | Download To be verified |
| 16 | Lecture 16 : Bayes Classifier V | Download To be verified |
| 17 | Lecture 17 : K Nearest Neighbor I | Download To be verified |
| 18 | Lecture 18 : K Nearest Neighbor II | Download To be verified |
| 19 | Lecture 19 : | Download To be verified |
| 20 | Lecture 20 | Download To be verified |
| 21 | Lecture 21 | Download To be verified |
| 22 | Lecture 22 : Support Vector Machine I | Download To be verified |
| 23 | Lecture 23 : Support Vector Machine II | Download To be verified |
| 24 | Lecture 24 : Support Vector Machine III | Download To be verified |
| 25 | Lecture 25 : Support Vector Machine IV | Download To be verified |
| 26 | Lecture 26 : Support Vector Machine V | Download To be verified |
| 27 | Lecture 27: Kernel Machines | Download To be verified |
| 28 | Lecture 28: Artificial Neural Networks I | Download To be verified |
| 29 | Lecture 29:Artificial Neural Networks II | Download To be verified |
| 30 | Lecture 30: Artificial Neural Networks III | Download To be verified |
| 31 | Lecture 31: Artificial Neural Networks IV | Download To be verified |
| 32 | Lecture 32: Clustering I | Download To be verified |
| 33 | Lecture 33: Clustering II | Download To be verified |
| 34 | Lecture 34: Clustering III | Download To be verified |
| 35 | Lecture 35: Clustering IV | Download To be verified |
| 36 | Lecture 36: Clustering V | Download To be verified |
| 37 | Lecture 37 : Regression I | Download To be verified |
| 38 | Lecture 38 : Regression II | Download To be verified |
| 39 | Lecture 39 : Regression III | Download To be verified |
| 40 | Lecture 40 : Regression IV | Download To be verified |
| 41 | Lecture 41 : Dimensionality Reduction - I | Download To be verified |
| 42 | Lecture 42 : Dimensionality Reduction - II | Download To be verified |
| 43 | Lecture 43 : Tutorial | Download To be verified |
| Sl.No | Language | Book link |
|---|---|---|
| 1 | English | Not Available |
| 2 | Bengali | Not Available |
| 3 | Gujarati | Not Available |
| 4 | Hindi | Not Available |
| 5 | Kannada | Not Available |
| 6 | Malayalam | Not Available |
| 7 | Marathi | Not Available |
| 8 | Tamil | Not Available |
| 9 | Telugu | Not Available |