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TensorFlow.js – Now Build Machine Learning Models in JavaScript!

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  • TensorFlow.js is an open source library that lets you build and train ML models in your browser
  • It’s available with GPU acceleration and also automaticlaly supports WebGL
  • You can import existing pre-trained models and also re-train entire existing ML models in the browser itself



If you’re a JavaScript developers who’s new to the world of Machine Learning, or a Machine Learning practitioner who’s new to JavaScript, this latest release of TensorFlow will intrigue you.

TensorFlow.js is an open-source library that you can use to train and build machine learning models in your web browser, using JavaScript and APIs. If you’re familiar with Keras, the high level layers API will seem very familiar to you.

You might be wondering at this point what’s the advantage here of using a browser to build ML models.

Well, running a ML program in your browser means there is need to install any libraries or drivers! Open your browser page and you’re ready to build your model. It’s also available with GPU acceleration. Additionally, TensorFlow.js supports WebGL, a JavaScript API that is used for rendering 2D and 3D graphics within any browser.

You can also open the webpage on your mobile or tablet which will enable your model to take advantage of sensor data.

You can import an existing pre-trained model and TensorFlow.js converters will make it browser ready for you. You can also re-train existing ML models using “transfer learning to augment an existing model trained offline using a small amount of data collected in the browser using a technique called Image Retraining”. You can re-train the model very quickly and efficiently with this while only requiring a small amount of data.


How do I install TensorFlow.js?

It’s pretty straightforward. You can use it by installing in from NPM:

yarn add @tensorflow/tfjs
npm install @tensorflow/tfjs
Or from script:
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]"></script>

Check out the TensorFlow.js website and their GitHub page to read more about this release.


Our take on this

This is awesome news for folks who are familiar with JavaScript and are trying to carve their way in the ML world! It makes things a lot simpler for folks coming from a non-ML background who are looking to understand this field. The use cases for this are plenty. I highly encourage you to check out the demos on the official site which include a real-time performance on a piano by a neural network and playing the popular Pac-Man game using images trained in a browser.

TensorFlow.js is basically the successor of deeplearn.js. The major difference between the two is the TensorFlow.js includes a layers API and imports pre-trained models and can also re-train them. Also, you can work on almost any GPU but it will not be close to the speed you’ll get on CUDA.

Are you planning to use this for building your models? What do you think about this latest TensorFlow release? Let us know in the comments section below!


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