DeepLearning.AI
Custom and Distributed Training with TensorFlow
DeepLearning.AI

Custom and Distributed Training 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

17,891 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.8

(379 reviews)

|

96%

Intermediate level

Recommended experience

24 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

4.8

(379 reviews)

|

96%

Intermediate level

Recommended experience

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

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

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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 4 modules in this course

This week, you will get a detailed look at the fundamental building blocks of TensorFlow - tensor objects. For example, you will be able to describe the difference between eager mode and graph mode in TensorFlow, and explain why eager mode is very user friendly for you as a developer. You will also use TensorFlow tools to calculate gradients so that you don’t have to look for your old calculus textbooks next time you need to get a gradient!

What's included

12 videos3 readings1 quiz1 programming assignment2 ungraded labs

This week, you will build custom training loops using GradientTape and TensorFlow Datasets. Being able to write your own training loops will give you more flexibility and visibility with your model training. You will also use a function to calculate the derivatives of functions so that you don’t have to look to your old calculus textbooks to calculate gradients.

What's included

8 videos2 readings1 quiz1 programming assignment2 ungraded labs

This week, you’ll learn about the benefits of generating code that runs in “graph mode”. You’ll take a peek at what graph code looks like, and you’ll practice generating this more efficient code automatically with TensorFlow’s tools, so that you don’t have to write the graph code yourself!

What's included

6 videos2 readings1 quiz1 programming assignment2 ungraded labs

This week, you will harness the power of distributed training to process more data and train larger models, faster. You’ll get an overview of various distributed training strategies and then practice working with two strategies, one that trains on multiple GPU cores, and the other that trains on multiple TPU cores. Get your cape ready, because you’re going to get some superpowers this week!

What's included

9 videos5 readings1 quiz2 programming assignments4 ungraded labs

Instructors

Instructor ratings
4.9 (69 ratings)
Laurence Moroney
DeepLearning.AI
15 Courses481,323 learners

Offered by

DeepLearning.AI

Recommended if you're interested in Machine Learning

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