Regression with Automatic Differentiation in TensorFlow faq

learnersLearners: 72
instructor Instructor: Amit Yadav instructor-icon
duration Duration: duration-icon

Learn how to use Automatic Differentiation in TensorFlow to quickly and accurately solve regression problems with this comprehensive online course.

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

Course Feature

costCost:

Paid

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

12th Jun, 2023

Course Overview

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

Updated in [August 31st, 2023]

What does this course tell?
(Please note that the following overview content is from Alison)
In this 15 hour long project-based course you will learn about constants and variables in TensorFlow you will learn how to use automatic differentiation and you will apply automatic differentiation to solve a linear regression problem By the end of this project you will have a good understanding of how machine learning algorithms can be implemented in TensorFlow

In order to be successful in this project you should be familiar with Python Gradient Descent Linear Regression

Note: This course works best for learners who are based in the North America region We're currently working on providing the same experience in other regions

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
By taking this course, learners will acquire skills and knowledge in constants and variables in TensorFlow, automatic differentiation, linear regression, Python, and Gradient Descent. They will be able to apply automatic differentiation to solve a linear regression problem and gain a good understanding of how machine learning algorithms can be implemented in TensorFlow. This course is best suited for learners based in the North America region.
lHow does this course contribute to professional growth?
This course provides professional growth by teaching learners how to use automatic differentiation and apply it to solve a linear regression problem. Learners will gain a good understanding of how machine learning algorithms can be implemented in TensorFlow. In order to be successful in this project, learners should be familiar with Python, Gradient Descent, and Linear Regression. This course works best for learners who are based in the North America region, but the same experience is being worked on for other regions.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education. It provides learners with a comprehensive understanding of how machine learning algorithms can be implemented in TensorFlow, and covers topics such as constants and variables, automatic differentiation, linear regression, and gradient descent. Learners should be familiar with Python prior to taking the course, and it works best for those based in the North America region.

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faq FAQ for Tensorflow Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a paid certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

Q2: How do I contact your customer support team for more information?

If you have questions about the course content or need help, you can contact us through "Contact Us" at the bottom of the page.

Q3: How many people have enrolled in this course?

So far, a total of 72 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q4: How Do I Enroll in This Course?

Click the"Go to class" button, then you will arrive at the course detail page.
Watch the video preview to understand the course content.
(Please note that the following steps should be performed on Coursera's official site.)
Find the course description and syllabus for detailed information.
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Add your desired course to your cart.
If you don't have an account yet, sign up while in the cart, and you can start the course immediately.
Once in the cart, select the course you want and click "Enroll."
Coursera may offer a Personal Plan subscription option as well. If the course is part of a subscription, you'll find the option to enroll in the subscription on the course landing page.
If you're looking for additional Tensorflow courses and certifications, our extensive collection at azclass.net will help you.

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