NILAY2233/Machine_Learning---Learning-Gradient-Descent-optimization-techniques

Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

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ChaitanyaC22/Deep-RL-Project---Maximize-total-profits-earned-by-cab-driver

The goal of this project is to build an RL-based algorithm that can help cab drivers maximize their profits by improving their decision-making process on the field. Taking long-term profit as the goal, a method is proposed based on reinforcement learning to optimize taxi driving strategies for profit maximization. This optimization problem is formulated as a Markov Decision Process i.e. MDP.

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MinhQuan-Github/Gradient-Descent

Gradient Descent with multiple method: Univariate - Multivariate, Momentum, Batch Gradient Descent, ...

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FatemaSamir/Optimization-Algorithms

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akshayratnawat/GradientDescent_Algorithms

This file explores the working of various Gradient Descent Algorithms to reach a solution. Algorithms used are: Batch Gradient Descent, Mini Batch Gradient Descent, and Stochastic Gradient Descent

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