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Dept     : CSE
Sem      : 5
Regul    : R2019
Faculty : Ms.S.R.Janani
phone  : NIL
E-mail  : jananiselvaraj.mit@gmail.com
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Announcements

  • Question Bank

    Dear Students the Question Bank has been uploaded for the following topics:</br>2 marks, </br>2 marks, </br>16 marks, </br>d

  • Assignment

    Assignment topic is Apriori Algorithm and due date is 28-09-2024.

  • Puzzles

    Dear Students the Puzzles has been uploaded for the following topics:</br>puzzles, </br>puzzles

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Subset Selection , </br>Introduction - Linear Models for Regression – Linear Regression Models and Least Squares , </br>Subset Selection

  • Resource Link

    Dear Students the Resource Link has been uploaded for the following topics:</br>subset selection</br>Machine learning</br>machine learning basics

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Machine Learning – perspective -Issues , </br>Examples of Machine Learning Applications , </br>Types of Machine Learning –Machine Learning process- preliminaries, testing , </br>Machine Learning algorithms, </br>Turning data into Probabilities, and Statistics for Machine Learning , </br>Probability theory -Bayesian Decision Theory., </br>Introduction - Linear Models for Regression – Linear Regression Models and Least Squares , </br>Subset Selection

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Shrinkage Methods – Derived Input Directions , </br>Linear Models for Classification- Discriminant Analysis , </br>Logistic Regression , </br>Separating Hyperplanes

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Shrinkage Methods – Derived Input Directions , </br>Linear Models for Classification- Discriminant Analysis , </br>Logistic Regression , </br>Separating Hyperplanes, </br>Boosting and Additive Trees – Boosting Trees – Regularization – Interpretation – Illustrations, </br>Neural Networks – Fitting Neural Network - Bayesian Neural Net, </br>Neural Network Representation – Problems – Perceptron , </br>Back Propagation Algorithms, </br>Multilayer Networks , </br>Case Study: Handwriting Recognition