Table of Contents
1. Introduction to Machine Learning
2. Naïve Bayes Algorithm
3. K-Nearest Neighbor Algorithm
4. Logistic Regression
5. Decision Tree Algorithm
6. Ensemble Models
7. Random Forest Algorithm
8. Boosting Algorithm
Annexure 1: Jupyter Notebook
Annexure 2: Python
Annexure 3: Singular Value Decomposition
Annexure 4: Preprocessing Textual Data
Annexure 5: Stemming and Lamentation
Annexure 6: Vectorizers
Annexure 7: Encoders
Annexure 8: Entropy
2. Naïve Bayes Algorithm
3. K-Nearest Neighbor Algorithm
4. Logistic Regression
5. Decision Tree Algorithm
6. Ensemble Models
7. Random Forest Algorithm
8. Boosting Algorithm
Annexure 1: Jupyter Notebook
Annexure 2: Python
Annexure 3: Singular Value Decomposition
Annexure 4: Preprocessing Textual Data
Annexure 5: Stemming and Lamentation
Annexure 6: Vectorizers
Annexure 7: Encoders
Annexure 8: Entropy