Popular GitHub Repositories for Classifying Forged

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

A collection of ChatGPT and GPT-3.5 instruction-based prompts for generating and classifying text.

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

?Getting started with TensorFlow: Classifying Text with Neural Networks

TensorFlow Implementation of the paper "End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures" and "Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths" for classifying relations

An example of how to use CreateML in Xcode 10 to create a Core ML model for classifying text

A PyTorch CNN for classifying the sentiment of movie reviews, based on the paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim (2014).

Classifying people as high risk and low risk based on their distance to other people.

A numpy based CNN implementation for classifying images

⚖️ Neural network for product matching, aka classifying whether two product titles represent the same entity

Google Street View House Number(SVHN) Dataset, and classifying them through CNN

Classifying Relations by Ranking with Convolutional Neural Networks

Public tutorials of using Flow Forecast for forecasting and classifying time series data

Convert lecture videos to notes using AI & machine learning. Code for the research titled "Lecture2Notes: Summarizing Lecture Videos by Classifying Slides and Analyzing Text using Machine Learning."

?? A simple Django web app classifying images using PyTorch.

A Python-based machine learning project for classifying Parkinson's disease using patient data and algorithms like XGBoost and Random Forest. Includes data preprocessing, feature analysis, and model evaluation with Scikit-learn and Pandas for accurate predictions.

Classifying Audio to Emotion

music generation with a classifying variational autoencoder (VAE) and LSTM

This sample project shows off how to prepare and deploy to Azure Web Apps a simple Python web service with an image classifying model produced in CNTK (Cognitive Toolkit) using FasterRCNN