Cost Function Exploration

This notebook explores the concept of the cost function in the context of machine learning. It provides an implementation of the cost function, examines its behavior with a small dataset, and includes an interactive contour plot where you can manipulate parameters (w and b) to observe their effects.

Overview

• Cost_Function_SoIn.ipynb: This Jupyter Notebook covers the implementation and exploration of the cost function.
• It includes interactive plots and detailed explanations about the impact of parameter changes on the cost function.

Features

• Cost function implementation with a small dataset.
• Interactive contour plot for parameter manipulation (numpy and matplotlib).
• Detailed explanation of the cost function, including formula and insights.
• 3D visualization of the cost function for enhanced understanding.

Instructions

1. Clone the repository to your local machine.

   git clone https://github.com/WahabMam/Loss-Cost-Function

Note

This notebook is derived from the Coursera Machine Learning Specialization course by Andrew Ng. You can refer to the course on Coursera for a more in-depth understanding.