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### In-depth study of Machine Learning Algorithms

- Linear Regression
- Logistic Regression
- Support Vector Machines
- Random Forest
- NaÃ¯ve Bayes Classification
- Ordinary Least Square Regression
- K-means
- Ensemble Methods
- Apriori Algorithm
- Principal Component Analysis
- Singular Value Decomposition
- Reinforcement or Semi-Supervised Machine Learning
- Independent Component Analysis

- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning

- Decision Trees
- Naive Bayes Classification
- Support vector machines for classification problems
- Random forest for classification and regression problems
- Linear regression for regression problems
- Ordinary Least Squares Regression
- Logistic Regression
- Ensemble Methods

- K-means for clustering problems
- Apriori algorithm for association rule learning problems
- Principal Component Analysis
- Singular Value Decomposition
- Independent Component Analysis