Keras Functional Model | How to build non-linear Neural Networks?
Channel: CampusX
Date: 2022-10-14

The Keras functional API is a way to create models that are more flexible than the Sequential API. The functional API can handle models with non-linear topology, shared layers, and even multiple inputs or outputs.

The main idea is that a deep learning model is usually a directed acyclic graph (DAG) of layers. So the functional API is a way to build graphs of layers.

Digital Notes for Deep Learning: https://shorturl.at/NGtXg

Codes:
https://colab.research.google.com/drive/1uCHf6hoLR1a-46RznVjqnhVZNechF0fz?usp=sharing
https://colab.research.google.com/drive/1pKfnYBal9HhuwRADU0FrWaVJ11_llk8-?usp=sharing
https://colab.research.google.com/drive/1B2azaSX9g55olY473c7WAMf3E5-717Ge?usp=sharing

Dataset Link:
https://www.kaggle.com/datasets/jangedoo/utkface-new

Blog:
https://machinelearningmastery.com/keras-functional-api-deep-learning/

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⌚Time Stamps⌚

00:00 - Intro
00:48 - The Problem with Sequential Model
07:35 - A Simple Example
09:01 - Code Implementation
15:29 - Complex Examples
17:56 - Multi Output Model
24:35 - Machine Learning Mastery Blog Post