Learn TensorFlow.js - Deep Learning and Neural Networks with JavaScript

From the creator

This full course introduces the concept of client-side artificial neural networks. We will learn how to deploy and run models along with full deep learning applications in the browser! To implement this cool capability, we’ll be using TensorFlow.js (TFJS), TensorFlow’s JavaScript library. By the end of this video tutorial, you will have built and deployed a web application that runs a neural network in the browser to classify images! To get there, we'll learn about client-server deep learning architectures, converting Keras models to TFJS models, serving models with Node.js, tensor operations, and more! This course was created by deeplizard. Check out their YouTube channel and website for more tutorials! 🦎 http://youtube.com/deeplizard http://deeplizard.com ⭐️Course Sections⭐️ ⌨️ 0:00 - Intro to deep learning with client-side neural networks ⌨️ 6:06 - Convert Keras model to Layers API format ⌨️ 11:16 - Serve deep learning models with Node.js and Express ⌨️ 19:22 - Building UI for neural network web app ⌨️ 27:08 - Loading model into a neural network web app ⌨️ 36:55 - Explore tensor operations with VGG16 preprocessing ⌨️ 45:16 - Examining tensors with the debugger ⌨️ 1:00:37 - Broadcasting with tensors ⌨️ 1:11:30 - Running MobileNet in the browser Keras model H5 files: VGG16 - https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5 MobileNet - https://github.com/fchollet/deep-learning-models/releases/download/v0.6

Published 2018-11-13 · Watch on YouTube ↗
Availability and playback restrictions are controlled by the original channel.