#tensorflow.js

[pythonandyou]

Machine Learning in JavaScript with TensorFlow.js ☞ http://dev.edupioneer.net/c8d28fcd9c #MachineLearning #JavaScript #TensorFlowjs

[pythonandyou]

Machine Learning In Node.js With TensorFlow.js ☞ http://dev.edupioneer.net/74c53f122f #MachineLearning #Nodejs #TensorFlowjs

[nodejsandyou]

Machine Learning In Node.js With TensorFlow.js ☞ http://dev.edupioneer.net/74c53f122f #MachineLearning #Nodejs #TensorFlowjs

[ankaapmo]

Build a Fully Functioning App Leveraging Machine Learning with TensorFlow.js - #Ankaa

Build a Fully Functioning App Leveraging Machine Learning with TensorFlow.js TensorFlow.js is a JavaScript library for training and deploying Machine Learning (ML) models in the browser (client-side) and on Node.js (server-side). In this article, I want to describe my experience in building an App (that I recently published on Google Play Store) with this javascript ML... https://ankaa-pmo.com/build-a-fully-functioning-app-leveraging-machine-learning-with-tensorflow-js/ #Deep_Neural_Network #Headlines_App #MachineLearning #Tensorflow #TensorflowJs #Web_App_Development

[ankaapmo]

GAN Lab: Generated Adversarial Networks In Your Browser! - #Ankaa

GAN Lab: Generated Adversarial Networks In Your Browser! This GitHub project is a highly interactive graphic demonstration of the features and operations of a generated adversarial network using TensorFow.js. It is based on work done by Minsuk Kahng, Nikhil Thorat, Duen Horng (Polo) Chau, Fernanda B. Viegas, and Martin Wattenberg in their paper: GAN... https://ankaa-pmo.com/gan-lab-generated-adversarial-networks-in-your-browser/ #Artifical_Intelligence #Gan_Lab #Generative_Adversarial_Network #TensorflowJs

[prostheticknowledge]

Real-time Human Pose Estimation in the Browser with TensorFlow.js

Machine Learning web demo from Google Creative Lab and Dan Oved can detect human poses via a webcam with web code:

In collaboration with Google Creative Lab, I’m excited to announce the release of a TensorFlow.js version of PoseNet¹,² a machine learning model which allows for real-time human pose estimation in the browser.

So what is pose estimation anyway? Pose estimation refers to computer vision techniques that detect human figures in images and video, so that one could determine, for example, where someone’s elbow shows up in an image. To be clear, this technology is not recognizing who is in an image — there is no personal identifiable information associated to pose detection. The algorithm is simply estimating where key body joints are.

Ok, and why is this exciting to begin with? Pose estimation has many uses, from interactive installations that react to the body to augmented reality, animation, fitness uses, and more. We hope the accessibility of this model inspires more developers and makers to experiment and apply pose detection to their own unique projects. While many alternate pose detection systems have been open-sourced, all require specialized hardware and/or cameras, as well as quite a bit of system setup. With PoseNet running on TensorFlow.js anyone with a decent webcam-equipped desktop or phone can experience this technology right from within a web browser. And since we’ve open sourced the model, Javascript developers can tinker and use this technology with just a few lines of code. What’s more, this can actually help preserve user privacy. Since PoseNet on TensorFlow.js runs in the browser, no pose data ever leaves a user’s computer.

You can find more background to the project here

You can try out the web demo yourself here