Tensorflow.js Making Predictions from 2D data

This exercise will demonstrate steps common to training many different kinds of models,Tensorflow js Making Predictions from 2D data but will use a small dataset and a simple (shallow) model. The primary aim is to help you get familiar with the basic terminology, concepts and syntax around training models with TensorFlow.js and provide a stepping stone for further exploration and learning.

Because we are training a model to predict continuous numbers, this task is sometimes referred to as a regression task. We will train the model by showing it many examples of inputs along with the correct output. This is referred to as supervised learning.

You will make a webpage that uses TensorFlow.js to train a model in the browser. Given "Horsepower" for a car, the model will learn to predict "Miles per Gallon" (MPG).

To do this you will:

Load the data and prepare it for training.

Define the architecture of the model.

Train the model and monitor its performance as it trains.

Evaluate the trained model by making some predictions.

Complete written explanation: https://onepagecode.substack.com/p/making-predictions-from-2d-data-using?sd=fs

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