softmax-classifier

amirhfarzaneh/lsoftmax-pytorch

The Pytorch Implementation of L-Softmax

srinadhu/CS231n

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

RubixML/HAR

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

ayesha92ahmad/SVM-Softmax-Classifier-CIFAR10-dataset

Read and process CIFAR10 dataset, implement SVM and Softmax classifiers, train , and also tune up hyper parameters.

elliotwaite/softmax-logit-paths

Plots how the logit values that are passed into the softmax function change over time as the model is trained.

gayanku/NBC-Softmax

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

Ishan7390/NN_fashMNIST

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

dlwsdqdws/MLP_Data_Classification

A data classification using MLP

KevinKiambe/DeepHistopathology

Deep Learning breast histology microscopy image recognition using Convolutional Neural Networks

neeraj1397/Radiography-Based-Diagnosis-Of-COVID-19-Using-Deep-Learning

Developed a Convolutional Neural Network based on VGG16 architecture to diagnose COVID-19 and classify chest X-rays of patients suffering from COVID-19, Ground Glass Opacity and Viral Pneumonia. This repository contains the link to the dataset, python code for visualizing the obtained data and developing the model using Keras API.

chrisshaffer/NN-character-recognition

Neural network-based character recognition using MATLAB. The algorithm does not rely on external ML modules, and is rigorously defined from scratch. A report is included which explains the theory, algorithm performance comparisons, and hyperparameter optimization.

DenryDu/cs231n_Assignment1

斯坦福大学cs231n课程的第一项作业之我的解答。Solution for Assignment1 (Images classification, kNN, SVM, SoftMax, FullyConnected Neural Network)

HillidatulIlmi/EDA-and-Deep-Learning-CNN-Fruit-Classification-Predictions

Classifying fruit types using a deep learning method, namely Convolutional Neural Network (CNN/ConvNet), which is a type of artificial neural network that is generally used in image recognition and processing. And carry out the process of improvement mode with transfer learning.

sashakttripathi/MNIST-Softmax-Classification

Image classifier which classifies MNIST database of handwritten digits 0-9 using 28x28 pixel images

Sitaras/Twitter-Covid-Vaccination-Data-Sentiment-Analysis

🦠| Sentiment analysis on tweets about covid-19 vaccinations using Soft-max Regression, FNN, RNN and BERT-Base-uncased.

AdityaTheDev/Covid-19-Prediction-Using-CNN

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 DeepNeuralNetwork. I found this image dataset(CT scan of patients) online and trained the model for 70 epochs using Softmax function in the output layer. If I had got a much more large image dataset(CT scan of patients) then I could have increased the accuracy a bit more. This model has the potential to become a breakthrough invention in the field of medical industry.

aswinrao/Breast-Cancer-Wisconsin-Diagnostic-Data-Set-Softmax-KNN-MLP

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.

FelixHo/Simple-ML-Algorithm

Simple implementation of general machine learning algorithms

gksoriginals/softmax-classifier-implementation

This is a naive implementaion of softmax classifier with cross entropy loss functioon

Harshpatel44/Softmax-classifier-Network

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

ndvinh98/CS331.K11-FlowersClassification

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

SameetAsadullah/cs231n-Softmax-Classifier-on-Cifar10-Dataset

Applied Softmax Classifier on Cifar10 Dataset

spsingh37/Image-classification

This project explores image classification on the PROPS Classification Dataset. It includes K-Nearest Neighbors, Support Vector Machine, and Softmax classifiers, and two-layer and multi-layer neural networks. The goal is to build a machine learning pipeline, experiment with optimizers, and evaluate model performance.

cryptomanic/DeepLearningBasics

Just exploring Deep Learning

jajokine/Digit-Recognizer

MITx - MicroMasters Program on Statistics and Data Science - Machine Learning with Python - Second Project

kirschte/dphelmet

Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers

MaliciousMonk45456/Customer-Segmentation

Applying a softmax based neural network to predict customer category

prachi220/Diabetic-Retinopathy-Detection

radoslawregula/iris-classification

Jupyter notebook implementing an efficient machine learning method to classify flowers from the Iris data set.

RanjeetKumbhar01/MNIST-Handwritten-Digits-Classification-using-Deep-Learning

MNIST Handwritten Digits Classification using Deep Learning with accuracy of 0.9944

aitorph7/supervMLpill

Introducción práctica al machine learning supervisado, explorando algunos de los algoritmos clásicos más utilizados.

jElhamm/Multiclass-SVM-Softmax-Classifier

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

JuanDa14Sa/Iris-Softmax-no-sklearn

Classifier Iris dataset with softmax from scratch

TiwariLaxuu/Pytorch-Practice

Yskandar/Softmax_classifier_and_KNN_from_scratch

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...).