cost-function

Demo for the part 2 of the tutorial on pychain

Interactive least-squares explorer: fit a line to noisy data and watch gradient descent cross the cost surface.

Implementation of necessary supervised machine learning algorithms for regression and classification.

A Python implementation of Gradient Descent for solving Multiple Linear Regression. This project demonstrates how the algorithm is used to minimize the Mean Squared Error (MSE) cost function and optimize the regression coefficients.

Implemented gradient descent and cost function for logistic regression from scratch using numpy

Linear Regression implementation based on the mathematical foundation

This project focuses on developing a Variational Quantum Circuit capable of performing Binary Classification between two classes: red wine and white wine, based on their characteristics using machine learning.

this repository is for the cosmology course in the Winter of 1401. you can find out your computational homework here.

A Python implementation of gradient descent for linear regression, visualized with cost function history, parameter trajectory, and a 3D cost surface.

Content: Classification, Sigmoid function, Decision Boundary, Cost function, Gradient descent, Overfitting, Regularisation

Repositori ini merupakan Bagian 01 dari seri pembelajaran "ML, DL, & RL", yang berfokus pada fondasi konseptual bagaimana sebuah model Machine Learning belajar dari data.

Mathematical implementation of supervised learning and gradient descent from scratch using Python and NumPy.

Machine_Learning_Stanford_Ng

A Mathematical Intuition behind Logistic Regression Algorithm

Analyzing factors leading to customers churning; predicting which customers' will churn?

Interactive demo of linear regression trained from scratch with manual gradient descent

From-scratch implementation of binary Logistic Regression using NumPy, with vectorized cost computation, gradient calculation, and batch gradient descent optimization.