Displaying 1 to 19 from 19 results

NSFW JS - NSFW detection on the client-side via TensorFlow.js

  •    Javascript

A simple JavaScript library to help you quickly identify unseemly images; all in the client's browser. NSFWJS isn't perfect, but it's pretty accurate (~90% with small and ~93% with midsized model)... and it's getting more accurate all the time.

tfjs-tiny-yolov2 - Tiny YOLO v2 object detection with tensorflow.js.

  •    TypeScript

JavaScript object detection in the browser based on a tensorflow.js implementation of tiny yolov2. The face detection model is one of the models available in face-api.js.

blue-cloud-mirror - Blue Cloud Mirror - IBM Cloud Technology Showcase

  •    Vue

This project contains a game where players need to show five specific emotions and do five specific poses in two levels. The fastest player wins. The game uses various key cloud technologies to demonstrate the value of a diverse, interconnected system, with both public and private cloud environments. Play the Game.

findme - serverless application to find unlabelled photos of you on twitter using machine learning (tensorflow

  •    Javascript

findme is a serverless application to find unlabelled photos of you on twitter using machine learning. Users provide a search query to retrieve tweets from the Twitter API. Face recognition is used to compare all faces found in the search results against the user's twitter profile image. Tweets with matching faces are shown in the client-side web application.




deep-learning-browser - Official repository of the book "Deep learning in the browser" published by Bleeding Edge Press August 2018

  •    Javascript

Official repository of the book Deep learning in the browser released August 2018 and published by Bleeding Edge Press. Here you will find all of the source code of the demos in the book. Clone the repo and all submodules.


metacar - A reinforcement learning environment for self-driving cars in the browser.

  •    TypeScript

Metacar is a 2D reinforcement learning environment for autonomous vehicles running in the browser. The project aims to let reinforcement learning be more accessible to everyone through solving fun problems. Metacar comes with a set of a predefined levels, some harder to address than others. More levels and possibile scenarios will be added soon (pedestrian, bikes...). Furthermore, the library let you create your own levels and personalize the environment to create your desired scenario. You can also take a look at the online demo.

Threepio - A multi-language library for translating commands between PyTorch, TensorFlow, and TensorFlow

  •    Python

Depending on your language, installation will differ. Use the package manager pip to install threepio.

handwritten-digit-recognition-tensorflowjs - In-Browser Digit recognition with Tensorflow

  •    Javascript

Digit recognition built with Tensorflow.js, Mnist dataset, React, Redux, Redux-Saga, Babel, Webpack, Styled-components, Eslint, Prettier and Ant Design. A demo is available at this location: https://digit-recognition.ixartz.com.

demos - Some JavaScript works published as demos, mostly ML or DS

  •    Javascript

Pull stock prices from online API and perform predictions using Recurrent Neural Network and Long Short-Term Memory (LSTM) with TensorFlow.js framework. Reinforcement learning algorithm for agents to learn the tic-tac-toe, using the value function. Train the agent to play tic-tac-toe, by having 2 agents play against each other through simulation. You can experiment by adjusting 2 parameters, 1) learning rate and 2) probability of exploration of each agent. After training, try playing against the agent.

textual-similarity-universal-sentence-encoder - Extract embeddings and group sentences with universal sentence encoder package from TensorFlow

  •    HTML

Extract embeddings and group sentences with universal sentence encoder package from TensorFlow.js. Try the textual similarity analysis web-app, and let me know how it works for you.

time-series-forecasting-tensorflowjs - Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow

  •    HTML

Disclaimer: As stock markets fluctuation are dynamic and unpredictable owing to multiple factors, this experiment is 100% educational and by no means a trading prediction tool. Before we can train the neural network and make any predictions, we will first require data. The type of data we are looking for is time series: a sequence of numbers in chronological order. A good place to fetch these data is the Alpha Vantage Stock API. This API allows us to retrieve chronological data on specific company stocks prices from the last 20 years. You may also refer to this article that explains adjusted stock prices, which is an important technical concept for working with historical market data.

enjoytheshow - Real-time facial expression gathering

  •    Javascript

This app uses face-api to gauge your facial expression, and then sends all faces in a particular URL or (room) to a "Watch" page. The watch page summarizes all the faces to a single Victory Pie chart. Runs the app in the development mode. Open http://localhost:3000 to view it in the browser.

rps_tfjs_demo - Training a Rock Paper Scissors model in the browser via TFJS - Learn along style

  •    Javascript

This project was bootstrapped with Create React App. Runs the app in the development mode. Open http://localhost:3000 to view it in the browser.

face-mask-detection - Real-time Face Mask Detection using TensorFlow and Keras.

  •    Jupyter

Python 3 -- for training the model. All the dependencies and required libraries are included in the file requirements.txt. You can install them by running pip install -r requirements.txt.

ngx-tfjs - 🤖 TensorFlow.js bindings for Angular

  •    TypeScript

This repository contains Angular bindings for TensorFlow.js models. You can find instructions how to use them here and a demo here.






We have large collection of open source products. Follow the tags from Tag Cloud >>


Open source products are scattered around the web. Please provide information about the open source projects you own / you use. Add Projects.