Machine Learning With Tensor Flow #1

Ashley Hendrickson

Ashley Hendrickson

- Software Engineer

Linear Regression.

With multiple inputs, we will use the following equation to measure the dot product:

First, let’s import our libraries we will be using tensorflow for our model. We will use numpy to properly format our data and matplotlib.pylot to print a graph

Let’s see what our predication is for 20 kilometers converted to miles:

This Post Has One Comment

  1. Мила

    The learning rate scheduler function takes in another function with the parameters of the number of epoch’s and the learning rate. An epoch represents the number of times all the training vectors are used to update the weights and biases. The schedule function is very useful for more complicated situations such as, for For every epoch this callback gets the updated learning rate value from the scheduler function. The current epoch and learning rate is then applied to the optimizers learning rate. The number of epochs isn’t super important the more epochs the more your weights will get updated and the longer your model will take to fit your data.

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