This project aims at implementing the Gradient Descent algorithm for Linear and Logistic regression. After implementing the algorithm, the focus shifts in deciphering the relationship between Cost and a variety of control parameters such as threshold, No. of iterations and alpha(learning parameter).
The project is divided into 4 experiments to understand the behaviour listed above, after which the results are visualized using plots and tables. The experiments are performed for Linear and Logistic Regression. After the experimentation, the project concludes with a detailed discussion and summary of the experiments, results and room for improvisation.
For further information, the Report available in the repository can serve as a good source.