DeepLearning.AI
Custom Models, Layers, and Loss Functions with TensorFlow
DeepLearning.AI

Custom Models, Layers, and Loss Functions with TensorFlow

This course is part of TensorFlow: Advanced Techniques Specialization

Taught in English

Some content may not be translated

Laurence Moroney
Eddy Shyu

Instructors: Laurence Moroney

33,057 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.9

(973 reviews)

|

96%

Intermediate level

Recommended experience

31 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.9

(973 reviews)

|

96%

Intermediate level

Recommended experience

31 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the TensorFlow: Advanced Techniques Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 5 modules in this course

Compare how the Functional API differs from the Sequential API, and see how the Functional API gives you additional flexibility in designing models. Practice using the functional API and build a Siamese network!

What's included

11 videos7 readings1 quiz1 programming assignment1 app item3 ungraded labs

Loss functions help measure how well a model is doing, and are used to help a neural network learn from the training data. Learn how to build custom loss functions, including the contrastive loss function that is used in a Siamese network.

What's included

9 videos3 readings1 quiz1 programming assignment3 ungraded labs

Custom layers give you the flexibility to implement models that use non-standard layers. Practice building off of existing standard layers to create custom layers for your models.

What's included

10 videos1 reading1 quiz1 programming assignment3 ungraded labs

You can build off of existing models to add custom functionality. This week, extend the TensorFlow Model Class to build a ResNet model!

What's included

7 videos3 readings1 quiz1 programming assignment2 ungraded labs

Custom callbacks allow you to customize what your model outputs or how it behaves during training. This week, implement a custom callback to stop training once the callback detects overfitting.

What's included

3 videos4 readings2 ungraded labs

Instructors

Instructor ratings
4.8 (310 ratings)
Laurence Moroney
DeepLearning.AI
15 Courses481,212 learners
Eddy Shyu
DeepLearning.AI
14 Courses834,936 learners

Offered by

DeepLearning.AI

Recommended if you're interested in Machine Learning

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