cost-function

Autonomous Vehicle modelling using MATLAB and Simulink

Implementation of soft dynamic time warping in pytorch

A dependency free library of standardized optimization test functions written in pure Python.

A very simple Genetic Algorithm implementation for matlab, easy to use, easy to modify runs fast.

🟣 Cost Function interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.

Economic Dispatching by Bees Algorithm

This repository provides a comprehensive machine learning course with theoretical concepts and practical implementations

This program implements logistic regression from scratch using the gradient descent algorithm in Python to predict whether customers will purchase a new car based on their age and salary.

building a deep neural network with as many layers as you want!

A from-scratch Linear Regression model optimized via Gradient Descent for house price prediction.

Here, we implement regularized linear regression to predict the amount of water flowing out of a dam using the change of water level in a reservoir. In the next half, we go through some diagnostics of debugging learning algorithms and examine the effects of bias v.s. variance.

Neural networks is a model inspired by how the brain works. It is widely used today in many applications: when your phone interprets and understand your voice commands, it is likely that a neural network is helping to understand your speech; when you cash a check, the machines that automatically read the digits also use neural networks.

Implementation is to use gradient descent to find the optimal values of θ that minimize the cost function.

Presentations And Source Codes of My Machine Learning Mini Course

Implement a safe autonomous navigation in a simulated 3D environment full of cars. Apply concepts like prediction, finite state machines, behavior planning, and more.

Monte-Carlo search for the minimum of the multidimensional "cost" function

Project for "Clustering" Master course of Data Science and Information Technologies (DSIT)

OpenLoss: This repository discloses cost functions designed for open-set classification tasks, namely, Entropic Open-set, ObjectoSphere and Maximal-Entropy Loss.

A Mathematical Intuition behind Linear Regression Algorithm