Machine learning algorithms in Dart programming language
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Updated
Sep 7, 2024 - Dart
Machine learning algorithms in Dart programming language
The Pytorch Implementation of L-Softmax
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.
本科毕业设计 - 基于数据解析的化工生产过程诊断
Read and process CIFAR10 dataset, implement SVM and Softmax classifiers, train , and also tune up hyper parameters.
Plots how the logit values that are passed into the softmax function change over time as the model is trained.
Code for the Paper : NBC-Softmax : Darkweb Author fingerprinting and migration tracking (https://arxiv.org/abs/2212.08184)
Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer
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.
A data classification using MLP
Deep Learning breast histology microscopy image recognition using Convolutional Neural Networks
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.
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.
🦠| Sentiment analysis on tweets about covid-19 vaccinations using Soft-max Regression, FNN, RNN and BERT-Base-uncased.
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)
Image classifier which classifies MNIST database of handwritten digits 0-9 using 28x28 pixel images
Applied Softmax Classifier on Cifar10 Dataset
Repository contains neural network for classification using softmax as an activation function
Classifying the following 5 types of flowers: Rose, Daisy, Dandelion, Sunflower and Tulip
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