Repository contains neural network for classification using softmax as an activation function

Applied Softmax Classifier on Cifar10 Dataset

Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer

In this project, I implement a softmax classifier and a K-nearest-neighbor algorithm from scratch and train them. I do not use any DL library, only classic math libraries are required (numpy, math, mathplotlib...).

Applying a softmax based neural network to predict customer category

Implementation of Deep Learning algorithm from scratch

Classifying the following 5 types of flowers: Rose, Daisy, Dandelion, Sunflower and Tulip

Compared 3 Machine learning algorithms namely Softmax classification, K nearest neighbours and Multilayer Perceptron using F-1 scoring on Breast Cancer Wisconsin dataset. Used Features based on digitized image of a fine needle aspirate (FNA) of a breast mass. Used Scikit SKLearn to Implement the 3 models.

"This program trains a model using 'SVM' or 'Softmax' and predicts the input data. Loss history and predicted tags are displayed as results."

A data classification using MLP

KNN, SVM, Neural network for image classification

Code Snippets for Sentiment Analysis Related Operations

Convolution Neural Network to predict Covid-19. This is a CNN model which predicts whether you have Healthy or you have Coronavirus or you have Pneumonia. I implemented CNN from Scratch and I implemented VGG-16 architecture. This model takes your CT scan report as input and will tell you the result. This Convolutional layer Connects to DeepNeura…

Code for the Paper : NBC-Softmax : Darkweb Author fingerprinting and migration tracking (https://arxiv.org/abs/2212.08184)

Image Classification pipeline for CIFAR-10 dataset based on K-NN, Svm, Softmax and 2-layer Neural Net Classifiers

Simple implementation of general machine learning algorithms

Classify an email as a ham or a spam.

MNIST Handwritten Digits Classification using Deep Learning with accuracy of 0.9944

My attempt to implement a generic deep learning platform using Python