63 ratings
4,407 already enrolled
Understanding tensor constants, and tensor variables in TensorFlow.
Understanding automatic differentiation in TensorFlow.
Using automatic differentiation to solve a linear regression problem in TensorFlow.
In this 1.5 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.
Mathematical Optimization
Machine Learning
Tensorflow
Linear Regression
Automatic Differentiation
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by TC
Apr 9, 2020A good hands on training platform for beginners. A very basic project for beginners to begin with.
by PM
Feb 28, 2021Another nice introduction to TensorFlow by Amit Yadav! Thanks for the project!
by PP
Oct 2, 2020Great Course. Would've liked if a more sophisticated example was taken instead of linear regression, but nonetheless, great.
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Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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