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Advanced Deep Learning with Keras
Intermediate
Updated 12/2024Start course for free
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PythonArtificial Intelligence4 hours13 videos46 exercises3,950 XP32,804Statement of Accomplishment
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Course Description
Keras functional API
In this course, you will learn how to solve complex problems using the Keras functional API.Beginning with an introduction, you will build simple functional networks, fit them to data, and make predictions. You will also learn how to construct models with multiple inputs and a single output and share weights between layers.
Multiple-input networks
As you progress, explore building two-input networks using categorical embeddings, shared layers, and merge layers. These are the foundational building blocks for designing neural networks with complex data flows.It extends these concepts to models with three or more inputs, helping you understand the parameters and topology of your neural networks using Keras' summary and plot functions.
Multiple-output networks
In the final interactive exercises, you'll work with multiple-output networks, which can solve regression problems with multiple targets and even handle both regression and classification tasks simultaneously.By the end of the course, you'll have practical experience with advanced deep learning techniques to advance your career as a data scientist, including evaluating your models on new data using multiple metrics.
Prerequisites
Introduction to Deep Learning with Keras1
The Keras Functional API
2
Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers
3
Multiple Inputs: 3 Inputs (and Beyond!)
4
Multiple Outputs
Advanced Deep Learning with Keras
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