TensorFlow.js – Running MobileNet in the browser

In this video, we’ll be adding enhancements and new functionality to our deep learning web application to increase its speed and performance. Specifically, we’ll see how we can do that by switching models. We currently have a web app that allows users to select and…

TensorFlow.js – Broadcasting tensors

In this video, we’ll learn about broadcasting and illustrate its importance and major convenience when it comes to tensor operations. Over the last couple of videos, we’ve immersed ourselves in tensors, and hopefully now, we have a good understanding of how to work with, transform,…

TensorFlow.js – Examining tensors with the debugger

In this video, we’re going to continue our exploration of tensors. Here, we’ll be stepping through the code we developed last time with the debugger to see the exact transformations that are happening to our tensors in real-time. Last time, we went through the process…

TensorFlow.js – Explore tensor operations through VGG16 preprocessing

In this video, we’re going to explore several tensor operations by preprocessing image data to be passed to a neural network running in our web app. Recall that last time, we developed our web app to accept an image, pass it to our TensorFlow.js model,…

TensorFlow.js – Loading the model into a neural network web app

In this video, we’ll continue the development of the client-side deep learning application we started in the last video. Recall, we previously built the UI for our CNN image classification web app that will first use VGG16 as the model. Now, we’ll focus on the…

TensorFlow.js – Building the UI for neural network web app

Now that we have Express set up to host a web app for us, let’s start building one! In this video, we’re going to begin building our first client-side neural network application using TensorFlow.js. With this app, a user will select an image, submit it…

TensorFlow.js – Serve deep learning models with Node.js and Express

In this video, we’ll go through the process of getting a web server set up to host deep learning web applications and serve TensorFlow.js models with Express for Node.js. To build deep learning applications that run in the browser, we need a way to host…

TensorFlow.js – Convert Keras model to Layers API format

In this video, we’ll continue getting acquainted with the idea of client-side neural networks, and we’ll kick things off by seeing how we can use TensorFlow’s model converter tool, tensorflowjs_converter, to convert Keras models into TensorFlow.js models. This will allow us to take models that…

Tensorflow.js – Introducing client-side neural networks

In this video, we’re going to introduce the concept of client-side artificial neural networks, which will lead us to deploying and running models, along with our full deep learning applications, in the browser. To implement this cool capability, we’ll be using Tensorflow.js (TFJS), Tensorflow’s Javascript…

Sign language image classification – Fine-tuning MobileNet with Keras

In this video, we’ll be building on what we’ve learned about MobileNet and the techniques we’ve used for fine-tuning to fine-tune MobileNet on a custom image data set that does not have classes similar to the ImageNet classes it was originally trained on. We saw…