Sequential Model - Keras
Here we go over the sequential model, the basic building block of doing anything that's related to Deep Learning in Keras. (this is super important to understand everything else that is coming after this in the series!)
I go over the two ways of declaring the functional signature (either way yields the exact same thing):
Way #1: Specifying a list of layers.
Way #2: Using the add method.
I then explain the segments of model compilation followed by model training after which I finally move onto model evaluation.
Links:
1) Link to my Scikit Learn tutorial - A Bit of DataScience and Scikit Learn: • Intro to Scikit Learn
2) The Hitchhiker's Guide to Python - one of the best handbooks to the installation, configuration, and usage of Python that I have come across: http://docs.python-guide.org/en/latest/
3) Link to Keras: https://keras.io
4) Link to TensorFlow: https://www.tensorflow.org
5) GitHub link to a-bit-of-deep-learning-and-keras notebooks: https://github.com/knathanieltucker/a...
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