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Deploying TensorFlow Models to a Web Application: Using Flask API, TensorFlowJS, and TensorFlow Serving

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Course Features

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Duration

38 minutes

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

38 minutes

Course Description

Machine learning is a way to harness the power of AI algorithms. Companies and developers often have difficulty deploying machine learning models efficiently. This is due to a lack of a proper process setup and execution. Vikraman created a step-by-step guide after receiving feedback from his YouTube subscribers. You'll learn how to deploy machine learning models in web apps using TensorFlow.js. These models can be deployed at scale, and you will learn how to use users' existing hardware like web cams to complete common machine learning tasks.

Course Overview

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International Faculty

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Deploy machine learning models at scale

Save, export, and restore machine learning models

Use Flask to work with TensorFlow and Keras models

Target Students

Engineers, coders, and researchers who wish to deploy machine learning models in web applications

A basic understanding of TensorFlow, Python, HTML and general machine learning and deep learning algorithms is helpful

Course Instructors

Vikraman Karunanidhi

Instructor

Vikraman Karunanidhi is the instructor for this course
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