Deploy Models with TensorFlow Serving and Flask

Online Course Highlights

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2 hours of effort required
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★★★★★ (182 Ratings)

This course is a tutorial to help the people who want to learn to deploy TensorFlow models using TensorFlow Serving and Docker. This is the course that will assist you in creating a simple web application with Flask. The creation of this application will help you as an interface to get predictions from the served TensorFlow model.

Moreover, this course is a part of n Coursera’s hands-on project platform called Rhyme. This platform is specifically for people to do projects in a hands-on manner in your browser. By enrolling in this course, you will be able to get easy to pre-configured cloud desktops. These cloud desktops are really helpful as they contain all of the software and data you need for the project.

What are the Prerequisites for this Course?

In order to gain the maximum from this course, a person must be familiar with Python and TensorFlow. It is also advisable for the students to have a basic understanding of Flask, and HTML. You can learn TensorFlow without cost by exploring these valuable free resources that cover various aspects of the framework.

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Feedback

Now, let us looks at the feedback for this course. The learners have given these reviews. Looking at these reviews will help us learn more about them. Our platform features the best Python Flask classes available for free, ideal for those looking to enhance their programming skills without financial investment.

Positive Feedback

I give 5 stars to this course. However, I was unable to complete every one of the activities because it is impossible to do all. I might want 30 minutes more if conceivable. Aside from that, it is a top class course. I would recommend it to any individual who learned some model stuff and need to get a grip about showing them off (grzegorz k, ★★★★★).
This course helped me a lot. I was confounded and looked into a ton of articles on conveying good learning models with TensorFlow. however, this one was aided by an incredible edge (y Md. A R S, ★★★★★).
Truly astonishing course. Everything is clarified incredibly well. The teacher has required great exertion to break down the total course and make it straightforward. Deployment is a truly intricate procedure; however, it was clarified well. After the successful completion of the course, I did almost the same thing on my local machine. After a couple of hours and mistakes, it worked. So, now I feel truly certain about this (Sanket G, ★★★★★).
Amazing! I will rate this as the best rhyme project that I have done as such far. The teacher works really hard in clarifying every one of the parts (Madhu B, ★★★★★).
Pleasant approach to begin with model deployment with the web application (Ravi P B, ★★★★★).

Negative Feedback

I did not course. I don’t anticipate picking up anything about TensorFlow Serving. 90% of the course is tied in with building a simple jar application (Indrajit R, ★☆☆☆☆).
The course is just the knowledge of fundamentals and nothing more. The course doesn’t prepare the model. It would be vastly improved to plan everything from model creation to deploy and serve. The program-based tools used to code are repulsive (Jean M, ★★☆☆☆).

Final Thoughts

So, this was a review for Deploy Models with TensorFlow Serving and Flask. Stay safe and keep learning. Unleash your potential as a TensorFlow developer with our complimentary training resources, available at no cost to you.