What you will build: You will make a webpage that uses TensorFlow.js to train a model in the browser. Given a black and white image of a particular size it will classify which digit appears in the image. The steps involved are:
- Load the data.
- Define the architecture of the model.
- Train the model and monitor its performance as it trains.
- Evaluate the trained model by making some predictions.
What you'll learn:
- TensorFlow.js syntax for creating convolutional models using the TensorFlow.js Layers API.
- Formulating classification tasks in TensorFlow.js
- How to monitor in-browser training using the tfjs-vis library.
What you'll need
- A recent version of Chrome or another modern browser that supports ES6 modules.
- A text editor, either running locally on your machine or on the web via something like Codepen or Glitch.
- Knowledge of HTML, CSS, JavaScript, and Chrome DevTools (or your preferred browsers devtools).
- A high-level conceptual understanding of Neural Networks. If you need an introduction or refresher, consider watching this video by 3blue1brown or this video on Deep Learning in Javascript by Ashi Krishnan.
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