Course10610685039 lectures
Predictive Modelling with Applications: Supervised and Unsupervised Learning
Prof. Sayantee Jana · IIT Hyderabad
Lectures
Week 1
- Introduction to Predictive Modelling
- Correlation coefficient
- Principal Components Analysis 1
- Principal Components Analysis 2
- Principal Components Analysis 3
Week 2
- Factor Analysis - 1
- Factor Analysis - 2
- Factor Analysis applications with R
- Introduction to Cluster Analysis
- Agglomerative Hierarchical clustering 1
Week 3
- Hierarchical clustering
- Hierarchical clustering using R examples
- k-means clustering
- Simple linear regression 1
- Simple linear regression 2
Week 4
- Multiple linear regression 1
- Multiple linear regression 2
- Multiple linear Regression 3
- Outliers 1
- Outliers 2
Week 5
- Outliers Detection
- Regression Modelling with Categorical predictors using R
- Modelling Non-linear and Interaction effects in Regression using R
- Autocorrelation 1
- Autocorrelation 2
Week 6
- Tests for Normality 1
- Tests for Normality 2
- Multicollinearity in Regression 1
- Multicollinearity in Regression 2
- Multicollinearity in Regression 3
Week 7
- Heteroscedasticity 1
- Heteroscedasticity 2
- Heteroscedasticity 3
- Variable Selection and Model Evaluation
- Case study
Week 8
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Hyderabad
- Department
- Computer Science and Engineering
- Teacher
- Prof. Sayantee Jana
- Level
- Undergraduate
- Language
- English
- Subjects
- Computer science, Engineering
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed
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