Lecture 60: Bias vs tradeoff|Ridge vs Lasso vs ElasticNet Regularization| L1 penalty| L2 penalty|VTU
Lecture 55: Problem on Linear regression|machinelearning|VTU|bds602|bcs602|bcm601|bai601
Lecture 42: Classical vs adaptive ML systems|Learning types|bcm601|bds602|bai602|bcs602
Lecture 14: UNIVARIATE DATA ANALYSIS & VISUALIZATION| bar |pie chart|histogram|bcm601|bds602|bcs602
Lecture 29: Parzen Window| BDS602|BC602| BCM601|machine learning|non parametric vs parametric models
Lecture 41:What is Learning|Types of Learning|Tom Mitchell definition of learning|BCM601|BDS602|VTU
Lecture 72: Clustering – Part 2|Key Problems associated with clustering of large data: Solved
Lecture 31:Module5| Python Class & Objects| mutable objects| aliasing | Copy module|__str__ method
Lecture 65: Problem: Apply C4.5 algorithm for set of continuous values for attribute CGPA|Discretize
Lecture 18: Problems |COVARIANCE | CORRELATION|PEARSON CORRELATION COEFFICIENT|BDS602|BCS602|BCM601
Lecture 70: TYPES OF NAÏVE BAYES CLASSIFIER|Force Bayes|Problem on Bayes optimal classifier|bcs602
Lecture 64: How to build decision tree using C4.5 algorithm|C4.5 decision tree algorithm|ML|BCS602
Lecture 35: Difference between correlation and covariance | variance vs correlation vs correlation
Lecture 74: Clustering – Part 4|Problem on Single linkage clustering or Min algorithm|bcs602|bds602
Lecture 33: T-test| Hypothesis test|independent t-test|paired test|sample test|bds602|bcs602|bcm601
Lecture 73: Clustering – Part 3|HIERARCHICAL CLUSTERING|agglomerative algorithms|TYPES OF LINKAGE
Lecture 59: Problem on Logistic Regression|Module 3|VTU|BDS602|BCS602|BAI602|BCM601
Lecture 79: Numerical on K-means algorithm with algorithm |BCM601|BDS602|BCS6-2|BAI60k-means|VTU
Lecture 15: Skewness, Kurtosis, Mean absolute deviation,coefficient of varation|BCM601|BDS602|BCS602
Lecture 20: Five point summary and Box plot with problem solving|BCM601|BDS602|BCS602
