softmax-regression

gyrdym/ml_algo

Machine learning algorithms in Dart programming language

myazi/myLearn

machine learning algorithm

hiroyuki-kasai/GDLibrary

Matlab library for gradient descent algorithms: Version 1.0.1

AFAgarap/wisconsin-breast-cancer

[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

VuBacktracking/Coursera-Machine-Learning-Specialization

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

jerett/Keras-CIFAR10

practice on CIFAR10 with Keras

SSQ/Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

Short description for quick search

JYNi16/Deeplearning-Beginner

Various Classical Deep-learning Algorithm coded by Tensorflow and Pytorch framework

waybarrios/TensorFlow_CNN

Example CNN on CIFAR-10 classification

priyanka-kasture/Handwritten-Digit-Recognizer

Handwritten Digit Recognition using Softmax Regression in Python

trqminh/softmax-regression

get familiar with pytorch

Armin-Abdollahi/Iris-Flower-Classification

arnejad/multiclass-classification

Implementation of multinomial logisitic regression, Weighted Logistic Regression, Bayesian Logistic Regression, Gaussian Generative Classification and Gaussian Naive Bayes Classification from scratch in MATLAB

pkluber/MoS-Tensorflow

Mixture of Softmaxes implementation in Tensorflow

williamd4112/simple-linear-classification

A python implementation of linear classification algorithm (including Probabilistic Generative Model, Probabilistic Discriminative Model). (See Pattern Recognition and Machine Learning, Bishop)

lochielochie/open-deep-research

An open source deep research clone. AI Agent that reasons large amounts of web data extracted with Firecrawl

Naman-ntc/CIFAR-10-Recognition

Image Recognition on the CIFAR-10 training set using various approaches like Convolutional neural networks, Support Vector Machines, Softmax regression using only Numpy

sunnysoni97/hand_reader

Handwriting Recognition Software (Python/AI/kivy)

Rebabit/Knowledge-Engineering

Projects for Knowledge Engineering class

spChalk/Vaccine-Sentiment-Classifier

: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.

xup6fup/MxNetR-examples

This project provides a series of MxNetR example for letting readers to get started quickly.

daodavid/maths-behind-ML

Maths behind machine learning and some implementations from scratch.

amanraj209/CIFAR10_Models

giannhskp/Artificial-Intelligence-II_Natural-Language-Processing

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)

itsatefe/Pattern-Recognition

Statistical Pattern Recognition (classic machine learning)

mrcaidev/statistic-learning-and-pattern-recognition

电子科技大学 2020 级《统计学习与模式识别》课程代码。

coderconroy/softmax-mnist-classifier

Softmax Regression applied to MNIST Handwritten Dataset

daodavid/classic-ML

Implementation of classic machine learning concepts and algorithms from scratch and math behind their implementation.Written in Jupiter Notebook Python

devil-cyber/MNIST-Fashion-Classification

MNIST Fashion Classifications using softmax regression

DhairyaC/Customer-Churn-Prediction

Analyze, visualize and predict customer churn using Machine Learning

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

Sentiment analysis on tweets about covid19 vaccinations with different methods.

Sagarnandeshwar/Naive_Bayes_And_Logistic_Regression_For_NLP

Applied Machine Learning (COMP 551) Project

tate8/softmax-regression

Softmax Regression from scratch. MNIST dataset

tdattm/wisconsin-breast-cancer-classification

Dự án này sử dụng các thuật toán machine learning bao gồm học có giám sát (KNN, hồi quy Logistic, SVM,...), học không giám sát (PCA, K-means) và các kỹ thuật giảm chiều để phân loại ung thư vú dựa trên bộ dữ liệu Wisconsin. Phù hợp để học tập về khoa học dữ liệu và ứng dụng thực tế trong phân tích dữ liệu y tế..

vectornguyen76/machine-learning-regression

Machine Learning Regression with Linear Regression, Logistic Regression and Softmax Regression