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

Machine learning algorithms in Dart programming language

Applying a softmax based neural network to predict customer category

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

A data classification using MLP

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

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

My attempt to implement a generic deep learning platform using Python

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)

MNIST Handwritten Digits Classification using Deep Learning with accuracy of 0.9944

Classifier Iris dataset with softmax from scratch

Applied Softmax Classifier on Cifar10 Dataset

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.

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

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

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...).

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.

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…

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.