Keras provides a quick way to implement, train, and evaluate robust neural networks in Python. Using Keras for AI development for prototyping AI is standard practice and AI practitioners need to know why and how to use Keras for particular AI implementations.
In this course, you'll explore advanced techniques for working with the Keras framework. You'll recognize how Keras is different from other AI frameworks and identify cases in which it is advantageous to use Keras. You'll examine the functionality of the Keras Sequential model and Functional API and the role of multiple deep learning layers present in Keras. Finally, you will work with practical AI projects developed using Keras and troubleshoot common problems related to model training and evaluation.
specify cases in which it is advantageous to use Keras over other platforms
compare and contrast Keras with MS CNTK
describe Keras Sequential model API and specify how it is used for developing AI
describe how to create more complex AI models using the Keras functional API
define core and convolutional layers, specifying their role in the overall neural network
define pooling and recurrent layers, specifying their role in the overall neural network
define the embedding layer, specifying its role in the overall neural network
specify multiple techniques and approaches to preprocessing provided by Keras
work with Keras to create and train a feedforward neural network model and demonstrate its performance
work with Keras evaluation tools to evaluate previously created neural networks
work with Python to conduct exploratory data analysis on sales data and troubleshoot creating and training a neural network in Keras using this data
work with Python to conduct exploratory data analysis on insurance premium data and troubleshoot creating and training a neural network in Keras using this data
work with Python to conduct exploratory data analysis on cancer patient data and troubleshoot creating and training a neural network in Keras using this data
work with Python to conduct exploratory data analysis for loan approval data and troubleshoot creating and training a neural network in Keras using this data