Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...

Abstract: Neural network related machine learning algorithms, inspired by biological neuron interaction mechanisms, are advancing rapidly in the field of computing. This development may be leveraged ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

1 School of Mechanical Engineering, Vellore Institute of Technology, Chennai, India 2 Centre for e-Automation Technologies, Vellore Institute of Technology, Chennai, India Introduction: Friction Stir ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...

Neural networks power today’s AI boom. To understand them, all we need is a map, a cat and a few thousand dimensions. Look at a picture of a cat, and you’ll instantly recognize it as a cat. But try to ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

The goal of a machine learning regression problem is to predict a single numeric value. Quantile regression is a variation where you are concerned with under-prediction or over-prediction. I'll phrase ...

Notifications You must be signed in to change notification settings Sales Forecasting for Retail Stores using Hybrid Neural Network and Sales affecting Variables Overview This project implements a ...