softmax-classifier

The Pytorch Implementation of L-Softmax

Machine learning algorithms in Dart programming language

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

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

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

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

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

Deep Learning breast histology microscopy image recognition using Convolutional Neural Networks

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)

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

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

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.

Simple implementation of general machine learning algorithms

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.

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

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.

One-vs-All Logistic Regression, Softmax Classifier, Gaussian Discriminative Analysis and Gaussian Naive Bayes

Softmax function based classification algorithm with MNIST dataset

Solutions for cs231n Standford Deep Learning course's assignment 1

Implementation of Deep Learning algorithm from scratch

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

KNN, SVM, Neural network for image classification

Code Snippets for Sentiment Analysis Related Operations

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

Classify an email as a ham or a spam.

Just exploring Deep Learning

Introduction to neural networks

rede neural totalmente conectada, utilizando mini-batch gradient descent e softmax para classificação no dataset MNIST

Algorithms for logistic regression, including regularization, soft-max loss and classifier