21 - Machine Learning Introduction
22 - Supervised Machine Learning
23 - Unsupervised Machine Learning
24 - Train Test Split
25 - Regression Analysis
26 - Linear Regression
26 - Linear-Regression.pptx
26 - Salary-Data.csv
26 - linear-regression.zip
27 - Logistic Regression
27 - Logistic-Regression.pptx
27 - logistic-regression-practical.zip
28 - KNN
28 - K-Nearest-Neighbors-KNN.pptx
28 - User-Data.csv
28 - knn-practical.zip
29 - SVM
29 - Support-Vector-Machine-SVM.pptx
29 - User-Data.csv
29 - svm-practical.zip
30 - Decision Tree
30 - Decision-Tree-Algorithm.pptx
30 - User-Data.csv
30 - decision-tree-practical.zip
31 - Random Forest
31 - Random-Forest-Algorithm.pptx
31 - User-Data.csv
31 - random-forest-practical.zip
32 - K Means Clustering
32 - K-Means-Clustering-Algorithm.pptx
32 - Mall-Customers.csv
32 - k-means-practical.zip
33 - GridSearchCV.pptx
33 - GridSearch CV
33 - gridsearch-cv.zip
