Friendly machine learning for the web! 🤖
-
Updated
Oct 11, 2024 - JavaScript
Friendly machine learning for the web! 🤖
🥕 Evolutionary Neural Networks in JavaScript
A Chrome Extension that promotes politically diverse news reading with Artificial Intelligence!
An Image captioning web application combines the power of React.js for front-end, Flask and Node.js for back-end, utilizing the MERN stack. Users can upload images and instantly receive automatic captions. Authenticated users have access to extra features like translating captions and text-to-speech functionality.
An experimental web text editor that runs a LSTM model while you write to suggest new lines
Tensorflow Node.js Examples
Find the origin of words in every language using a Deep Neural Network trained to create an etymological map.
Tesseract OCR implementation in React JS
💵 Using word2vec to predict trends in cryptocurrency.
Yeezy Taught Me Text Generation. Training next character predictions RNN LSTM model with user input text corpus
基于双向双层、引入注意力机制的LSTM对英雄联盟比赛胜率进行预测。
Borealis AI mentored water consumption prediction machine learning web application!
[This project is under code refactoring] A MERN project combining machine learning and logistic regression to classify financial news articles and forecast stock price trends
Open-source: AI powered business names generator. Proof of concept.
🤖 (WIP) Blogging and creative writing with a touch of AI.
Finding the intensity of emotions in tweets (SemEval 2018 Task 1 Participant)
This deep learning model uses a CNN-LSTM architecture to predict whether a given domain name is genuine or was artificially generated by a DGA.
PredictBay is an innovative project that aims to revolutionize decision-making in investment strategies through intelligent forecasting. Our platform utilizes advanced machine learning algorithms to provide accurate predictions for stocks from all over the world.
자리있어? - 경기도 광역버스 좌석예측 시스템
Add a description, image, and links to the lstm topic page so that developers can more easily learn about it.
To associate your repository with the lstm topic, visit your repo's landing page and select "manage topics."