Multi-class confusion matrix library in Python

Fast and customizable framework for automatic ML model creation (AutoML)

Deep Learning sample programs using PyTorch in C++

Automation framework for machine learning, forecasting, model evaluation, and interpretation.

An (unofficial) implementation of Focal Loss, as described in the RetinaNet paper, generalized to the multi-class case.

2017-CCF-BDCI-让AI当法官(初赛)：7th/415 (Top 1.68%)

A bidirectional LSTM with attention for multiclass/multilabel text classification.

This library has been moved to https://github.com/ntumlgroup/LibMultiLabel

Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0

Multiclass classification of vibration signals of faulty bearings

AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset

Classy-fire is multiclass text classification approach leveraging OpenAI LLM model APIs optimally using clever parameter tuning and prompting.

Image classification on Tiny ImageNet

Implementation of Focal Loss (Lin et al., 2017, Facebook AI Research) for handling class imbalance by focusing learning on hard, misclassified examples.

Multiclass Naive Bayesian Classification

Multiclass image classification using Convolutional Neural Network

The purpose of this project's design, development, and structure is to create an end-to-end Machine Learning Operations (MLOps) lifecycle to classify an individual's level of obesity based on their physical characteristics and eating habits.

Code for BERT classifier finetuning for multiclass text classification

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Balanced Multiclass Image Classification with TensorFlow on Python.

Python library for morphological cleaning of multiclass 2D numpy arrays (edge smoothing and island removal

TensorFlow in Practice Specialization. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forecasting 😀 All while having fun learning and participating in our Deep Learning Trivia games 🎉 http://bit.ly/deep-learning-tf

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

Hierarchical self-organizing maps for unsupervised pattern recognition

Automate detection of different emotions from paragraphs and predict overall emotion.

This repository contains code for implementing multi class semantic segmentation (specifically applied to satellite image classification) with PyTorch implementation of UNet.

(Python, R) Cost-sensitive multiclass classification (Weighted-All-Pairs, Filter-Tree & others)

"20 newsgroups" dataset - Text Classification using Multinomial Naive Bayes in Python.

use google pre-training model bert to fine-tuning for the chinese multiclass classification

This POC is using CNTK 2.1 to train model for multiclass classification of images. Our model is able to recognize specific objects (i.e. toilet, tap, sink, bed, lamp, pillow) connected with picture types we are looking for. It plays a big role in a process which will be used to classify pictures from different hotels and determine whether it's a picture of bathroom, bedroom, hotel front, swimming pool, bar, etc.