Machine Learning

Hello Everyone, this is my Machine Learning modules I have implemented so far.

Supervised Learning Modules

• Simple Linear Regression

  • A simple linear regression model to predict values based on a linear relationship between variables.

• Support Vector Regression

  • A support vector machine algorithm for regression tasks, handling both linear and non-linear data.

• Decision Tree Regression

  • A regression model that uses a decision tree to predict outcomes by learning decision rules from features.

• Random Forest Regression

  • An ensemble method using multiple decision trees to improve the accuracy and robustness of predictions.

• Logistic Regression

  • A statistical model for binary classification tasks, estimating probabilities using a logistic function.

• K Nearest Neighbor

  • A non-parametric method used for classification and regression by comparing a point to its k-nearest neighbors.