There are 1 repository under softmax-regression topic.
Code and data for the research paper "Towards Open Set Deep Networks" A Bendale, T Boult, CVPR 2016
Machine learning algorithms in Dart programming language
Matlab library for gradient descent algorithms: Version 1.0.1
[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset
practice on CIFAR10 with Keras
Short description for quick search
Example CNN on CIFAR-10 classification
Various Classical Deep-learning Algorithm coded by Tensorflow and Pytorch framework
Handwritten Digit Recognition using Softmax Regression in Python
get familiar with pytorch
Mixture of Softmaxes implementation in Tensorflow
Implementation of multinomial logisitic regression, Weighted Logistic Regression, Bayesian Logistic Regression, Gaussian Generative Classification and Gaussian Naive Bayes Classification from scratch in MATLAB
Image Recognition on the CIFAR-10 training set using various approaches like Convolutional neural networks, Support Vector Machines, Softmax regression using only Numpy
Contains Optional Labs and Solutions of Programming Assignment for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2023) by Prof. Andrew NG
A python implementation of linear classification algorithm (including Probabilistic Generative Model, Probabilistic Discriminative Model). (See Pattern Recognition and Machine Learning, Bishop)
Projects for Knowledge Engineering class (BIT北理工, NLP, 知识工程)
This project provides a series of MxNetR example for letting readers to get started quickly.
Maths behind machine learning and some implementations from scratch.
:syringe: Vaccine Sentiment Classifier is a deep learning classifier trained on real world twitter data, that distinguishes 3 types of tweets: Neutral, Anti-vax & Pro-vax.
Handwriting Recognition Software (Python/AI/kivy)
Sentiment Classifier using: Softmax-Regression, Feed-Forward Neural Network, Bidirectional stacked LSTM/GRU Recursive Neural Network, fine-tuning on BERT pre-trained model. Question Answering using BERT pre-trained model and fine-tuning it on various datasets (SQuAD, TriviaQA, NewsQ, Natural Questions, QuAC)
Statistical Pattern Recognition (classic machine learning)
电子科技大学 2020 级《统计学习与模式识别》课程代码。
Implementation of classic machine learning concepts and algorithms from scratch and math behind their implementation.Written in Jupiter Notebook Python
MNIST Fashion Classifications using softmax regression
MNIST Softmax regression implemion using only pure Python
Sentiment analysis on tweets about covid19 vaccinations with different methods.
Flexible SVM framework implementation
Applied Machine Learning (COMP 551) Project
Softmax Regression from scratch. MNIST dataset
Machine Learning Regression with Linear Regression, Logistic Regression and Softmax Regression