Inside TensorFlow: tfKeras (Part 1) faq

instructor Instructor: TensorFlow instructor-icon
duration Duration: 1.00 duration-icon

This course introduces the Keras architecture and its layers. It explains what a layer does and does not do, and provides examples of the most basic layer and a canonical lazy layer. It also covers nested layers and how to define losses on the fly and collect metrics. Finally, it demonstrates how to use layers in a model.

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Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Free

providerProvider:

Youtube

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

On-Demand

Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [February 21st, 2023]

This course provides an in-depth look at the TensorFlow Keras API, which is a high-level API for building and training deep learning models. It covers the architecture of Keras, the different types of layers, how to define losses, how to make layers serializable, and how to use the Functional API to create directed acyclic graphs of layers.
Possible Development Paths include becoming a deep learning engineer, a machine learning engineer, or a data scientist. Learners can also pursue further education in the field of artificial intelligence or computer science.
Learning Suggestions for learners include taking courses on machine learning, deep learning, and artificial intelligence. Learners should also become familiar with the TensorFlow library and its various APIs. Additionally, learners should practice building and training models using the Keras API.

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faq FAQ for Tensorflow Courses

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