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How to Integrate TensorFlow Model in Angular Application?

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The code that accompanies this article can be downloaded here. Couple of months back we investigated parts of TensorFlow's ecosystem beyond standard library. To be more precise, we investigated TensorFlow.js and how you can build and train models in the browser and/or in the Node.js. However, we didn't manage one important topic – integration. What we want to cover in this article is what happens when you have a neural network built and trained using TensorFlow and Python, and you have to integrate it in one Angular application.


Machine Learning In Node.js With TensorFlow.js - James Thomas

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TensorFlow.js is a new version of the popular open-source library which brings deep learning to JavaScript. Developers can now define, train, and run machine learning models using the high-level library API. Pre-trained models mean developers can now easily perform complex tasks like visual recognition, generating music or detecting human poses with just a few lines of JavaScript. Having started as a front-end library for web browsers, recent updates added experimental support for Node.js. This allows TensorFlow.js to be used in backend JavaScript applications without having to use Python.


Machine learning in the browser with TensorFlow.js

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Recently, more and more attention has been paid to artificial intelligence and machine learning. It would seem that these concepts are completely unrelated to web development and JavaScript technologies. They are usually associated with Python/R environment or even C libraries. One of the most popular frameworks used by an ever-increasing number of developers is TensorFlow. It was developed in Google in 2011.


Best JavaScript machine learning libraries in 2021 - LogRocket Blog

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JavaScript needs no special introduction -- it's one of the most popular cross-platform languages among web developers. And while some people consider it only a language for frontend development, JavaScript acts as an all-purpose programming language nowadays, and its possibilities are endless. Looking for the top JavaScript libraries that you can use in your Machine Learning projects? Synaptic is a well-known JavaScript neural network library created by MIT that can be used with Node.js or the browser. One significant feature of this library is its ability to build and train any first-order or second-order neural network architecture due to its architecture-free algorithm and pre-manufactured structure.


Build a simple Neural Network for Breast Cancer Detection using Tensorflow.js

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There's more and more research done on detecting all types of cancers in early stages and thus increasing probability of survival. Since I've been passionate about machine learning for a while, I decided to bring my own contribution to this research and learn to train my own neural network detection model. The twist was to build it using Tensorflow with JavaScript, not with Python. We're also using React to manage the state and display the data we get back from the model. For this tutorial, I chose to work with a breast cancer dataset.