The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems.
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About this Course
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Intermediate Level
Approx. 7 hours to complete
English
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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 7 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
2 hours to complete
Introduction
2 hours to complete
5 videos (Total 28 min), 2 readings, 5 quizzes
1 hour to complete
Supervised Learning Models
1 hour to complete
3 videos (Total 22 min)
2 hours to complete
Supervised Learning Models (Cont'd)
2 hours to complete
4 videos (Total 22 min)
1 hour to complete
Unsupervised Deep Learning Models
1 hour to complete
2 videos (Total 10 min)
Reviews
- 5 stars61.88%
- 4 stars23.48%
- 3 stars9%
- 2 stars2.81%
- 1 star2.81%
TOP REVIEWS FROM BUILDING DEEP LEARNING MODELS WITH TENSORFLOW
by XHJun 29, 2020
The course concepts are not in-depth enough, and the server for Jupyter notebook running is way too slow...
by LDNov 5, 2019
course needed to be updated for labs. Now Google moved to Tensorflow 2.0 this year.
by SMJun 4, 2022
Was a really fun course, but the final assignments were very lengthy.
by PCMar 31, 2020
The coding part was hard to understand. If that part could also be covered in videos as a tutorial.
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