Basic Machine Learning Tutorial using Python and R.

1. categorical_data
2. data_preprocessing

1. Simple Linear Regression
2. Multiple Linear Regression
3. Polynomial Regression
4. SVR
5. Decision Tree Regression
6. Random Forest Regression
7. Regression Template

1. Logistic Regression
2. KNN
3. SVM
4. Kernel - SVM
5. Naive Bayes
6. Decision Tree Classification
7. Random Forest Classification
8. Classification Template

1. K-means Clustering
2. Hierarchical Clustering

1. Apriori
2. Eclat

1. Upper Confidence Bound (UCB)
2. Thompson Sampling

1. NPL
2. NPL using google's BERT model

1. Artificial Neural Network (ANN)
2. Convolution Neural Network (CNN)

1. Principle Component Analysis (PCA)
2. Linear Discriminant Analysis (LDA)
3. Kernel-PCA

1. Comparing performance of regression models
2. Comparing performance of classification models
3. k-fold CrossValidation
4. Grid Search
5. XG Boost
6. CatBoost