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This 2-day, hands-on TensorFlow and Keras course covers the development of a real-world application powered by TensorFlow and Keras. You'll get a hands-on introduction to TensorFlow and Keras, including model architecture and evaluation. By the end of the course, you will deploy the model as a real-world product: a web application (with an HTTP API) that uses Flask to make our model predictions available to the world.
TensorFlow is a popular software created by Google (and open source contributors) to facilitate the development of machine learning applications, particularly those that use deep learning. Keras is an interface that facilitates the development of deep learning models. If you are a developer, analyst, or data scientist interested in developing applications using TensorFlow and Keras, this course will give you the start you need.
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Apr 14 - 15 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Reserve Your Seat
May 26 - 27 9:00 AM - 4:30 PM EDT Ottawa / Online (AnyWare) Reserve Your Seat
Jun 22 - 23 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) Reserve Your Seat
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Sep 21 - 22 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) Reserve Your Seat
Oct 19 - 20 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Reserve Your Seat
Nov 16 - 17 9:00 AM - 4:30 PM EST Ottawa / Online (AnyWare) Reserve Your Seat
Guaranteed to Run
When you see the "Guaranteed to Run" icon next to a course event, you can rest assured that your course event — date, time — will run. Guaranteed.This course is designed for developers, analysts, and data scientists interested in developing applications using TensorFlow and Keras.
TensorFlow is an open source library for numerical computation and it is used for large-scale machine learning. It uses Python as a front-end API for building applications with the framework, while executing those applications in high-performance C++.
Keras is a leading High-level API. It is written in python and was created to be user friendly and modular.
Keras is a high level library that cannot live on it's own, while TensorFlow is a framework that can live on it's own.
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