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…

Train neural network using transfer learning – Fine-tuning MobileNet with Keras

In this video, we’ll be training our fine-tuned MobileNet model on images from our own data set, and we’ll also be evaluating the model by using it to predict on unseen images. From the work we did together in the last video, we now have…

Build a fine-tuned MobileNet model with Keras

Now that we’ve seen what MobileNet is all about in our last video, let’s talk about how we can fine-tune the model via transfer learning and and use it on another dataset. We’ll also be walking through the implementation of this in code using Keras,…

MobileNet Image Classification with Keras

In this video, we’re going to introduce MobileNets, a class of light weight deep convolutional neural networks (CNN) that are vastly smaller in size and faster in performance than many other popular models. We’ll also see how we can work with MobileNets in code using…

Deploy Keras neural network to Flask web service | Part 9 – Information Privacy, Data Protection

In this video, we’re going to talk about a key point to consider when deploying a neural network, and that’s information privacy and data protection. So far in this series, we’ve covered several bases for deploying a deep learning model to a web service, and…

Convert decimal to binary using Javascript | Text to binary with code

In the text-to-binary video, we saw how to go from text, to character codes, to binary numerals. In this video, we are going to see how this works behind the scenes using JavaScript. Understanding how we can go from text to binary is pretty straight…

Deploy Keras neural network to Flask web service | Part 8 – Access model from Powershell, Curl

In this video, we’re going to explore how we can get predictions from our Keras model in a slightly different way than how we’ve seen it done in the browser. Here, we’ll be calling our back end Flask web service from both Powershell on Windows,…