Simple MLP (Multi-Layer Perceptron) framework with MNIST example

Uses algorithms like SNN, KNN, Naive Bayes, Decision Tree, VADER, and BERT to analyse the intricate language used in Shopee reviews, ensuring accurate interpretation of sentiments for Malaysia Rojak.

Single perceptron neural network , capacble of add . sub, mul and div from training data

This repository contains implementations of various machine learning algorithms done from scratch by me.

simple neural network implementation in python

Simple no dependency neural network framework

Pure Python Simple Neural Network (SNN) library

Neural networks built from scratch for MNIST digits classification

Creation of a simple neural network, which learns through trial and error, what result it should give for different first degree formulas. Technologies and languages used: TensorFlow, Keras and Python. Own learning.

Sentiment analysis using different types of deep neural networks.

Get started with Tensorflow/Keras API.

A Shallow Neural Network Using IRIS Dataset for Classifying Species.

When given an input (three numbers all either 0 or 1) the neural network will get an output, which should be the first of the three numbers.

This repository contains assignment, workshops and their solutions for one of my postgraduate subjects of COMP SCI 7315 - Computer Vision. The programming language is Python and report is written in LateX.

Java class for easily creating, training, and testing neural networks. Simply specify the network's structure and parameters and add data -- the rest is done for you!

Projects with simple neural networks