multiclass-classification

Multi-class confusion matrix library in Python

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

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, recommenders, and EDA.

Deep Learning sample programs using PyTorch in C++

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

Balanced Multiclass Image Classification with TensorFlow on Python.

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

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

Hierarchical self-organizing maps for unsupervised pattern recognition

alternative illustration2vec implitation of sigmoids of fully connected layer

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

XGBoost Medium article code

Multiclass image classification using Convolutional Neural Network

Image classification on Tiny ImageNet

Practical ML and NLP with examples.

This repository is containing an object classification & localization project for SINGLE object.

Reservoir computing library for .NET. Enables ESN , LSM and hybrid RNNs using analog and spiking neurons working together.

A case study on Pfam dataset to classify protein families.

[WIP] In this repository I implemented all assignments in python. (No octave to python library)

The Deakin Simpsons challenge 2021 is a computer vision competition for which the goal is to recognize Simpsons characters individually in images using machine learning/deep learning. The challenge is designed to provide students with the opportunity to work as team members, to compete with each other, and to enhance the student learning experience by improving their AI modeling, problem-solving, and team-working skills.

Implementation of Very Deep Convolutional Neural Network paper

A Generalized Multiclass Support Vector Machine

Multiple Class Flower Image Classification CNN using Keras

An SVM model for multi-class classification of Thyroid data.

Multi-Class Classification | Transfer Learning With PySpark

User-shelf interaction classification

This Problem is based on a Image Data set consisting of different types of weeds, to detect them in crops and fields. I have used Deep Learning Model called CNN(Convolutional Neural Networks) with Dropout, Batch Normalization, ReduceLearning rate on plateau, Early stoppig rounds, and Transposd Convolutional Neural Networks.