Regression with Automatic Differentiation in TensorFlow

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Rhyme
В этом Guided Project вы:

Understanding tensor constants, and tensor variables in TensorFlow.

Understanding automatic differentiation in TensorFlow.

Using automatic differentiation to solve a linear regression problem in TensorFlow.

Clock1.5 hours
BeginnerНачинающий
CloudЗагрузка не требуется
VideoВидео на разделенном экране
Comment DotsАнглийский
LaptopТолько для ПК

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.

Навыки, которые вы получите

Mathematical OptimizationMachine LearningTensorflowLinear RegressionAutomatic Differentiation

Будете учиться пошагово

На видео, которое откроется рядом с рабочей областью, преподаватель объяснит эти шаги:

  1. Tensor Constants

  2. Tensor Variables

  3. Automatic Differentiation

  4. Watching Tensors

  5. Persistent Tape

  6. Generating Data for Linear Regression

  7. Linear Regression

How Guided Projects work

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На разделенном экране видео преподаватель предоставляет пошаговые

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