Keras Basics Part 2 Tutorial 

In Keras Basics Part 1, You will learn how to load the dataset with the help of Pandas, How to split the dataset, scaling the test, and train data samples.

For Dataset download here:- http://www.mediafire.com/file/cw9c9v7uwyq6ylr/fake_reg.csv/file

For Entire Keras Parts 

Code:- http://www.mediafire.com/file/chs96g7e0oi3l6q/Keras_basics_pdf.pdf/file

Keras Basics Part 2 is a continuation of Part 1, In this Part, you will learn about model connection, etc. 

Importing the Sequential model and Dense layer based on the dataset, I imported these packages.

There are two methods to connect layers, you will clearly show in the video. Observe how many neurons are giving to connect from one layer to another layer.

After the connection completed, we will be going to perform model.compile(). In this compile(), we are going to pass the optimizer and loss. There are different optimizers are available. Based on our dataset I am considering rmsprop optimizer and mean square error. 

After completion of the compile, we will be going to perform model.fit(). Here we are giving to the number epochs. Based on your neuron number, you can decide your own to give a number of epochs.

I am giving 250 epochs, observe loss at each epoch.

You just need to remember steps,