In this video, we're going to talk about more general, non-sequential models in Keras using the functional API.
So there are two types of models in Keras. We've seen the sequential already. There is another type called model, which you would use if you were in need of non-sequential models. Once defined, we will see how to do that in just a second. The model can be trained and evaluated exactly like sequential models. So you don't have to learn anything about that part.
Using the functional API, you would usually start with the model and configure one or several inputs. Once you have those inputs defined, we define transformations for those inputs, until you arrive at one or several outputs.
The initial lectures series on this topic can find in the below links:
Cloud Architectures for AI and Deep Learning
• Cloud Architectures for AI and Deep Learning
Linear algebra
• Linear algebra
Deep feedforward neural networks
• Deep feed forward neural networks
Convolutional Neural Networks
• Convolutional Neural Networks
Recurrent neural networks
• Recurrent neural networks
LSTMs
• LSTMs
Autoencoders and representation learning
• Auto encoders and representation learning
Methods for neural network training
• Methods for neural network training
Gradient Descent Updater Strategies
• Gradient Descent Updater Strategies
How to choose the correct activation function
• How to choose the correct activation function
The bias-variance tradeoff in deep learning
• The bias-variance tradeoff in deep learning
Introduction to TensorFlow
• Introduction to TensorFlow
Neural Network Debugging with TensorBoard
• Neural Network Debugging with TensorBoard
Automatic Differentiation
• Automatic Differentiation
Introduction to Keras
• Introduction to Keras
Keras overview
• Keras overview
Sequential models in Keras
• Sequential models in keras
Feed-forward networks
• Feed forward networks
Recurrent neural networks
• Recurrent neural networks
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