Back to TensorFlow for CNNs: Learn and Practice CNNs
Learner Reviews & Feedback for TensorFlow for CNNs: Learn and Practice CNNs by Coursera Project Network
42 ratings
About the Course
This guided project course is part of the "Tensorflow for Convolutional Neural Networks" series, and this series presents material that builds on the second course of DeepLearning.AI TensorFlow Developer Professional Certificate, which will help learners reinforce their skills and build more projects with Tensorflow.
In this 2-hour long project-based course, you will learn the fundamentals of CNNs, structure, components, and how they work, and you will learn practically how to solve an image classification deep learning task in the real world and create, train, and test a neural network with Tensorflow using real-world images, and you will get a bonus deep learning exercise implemented with Tensorflow. By the end of this project, you will have learned the fundamentals of convolutional neural networks and created a deep learning model with TensorFlow on a real-world dataset.
This class is for learners who want to learn how to work with convolutional neural networks and use Python for building convolutional neural networks with TensorFlow, and for learners who are currently taking a basic deep learning course or have already finished a deep learning course and are searching for a practical deep learning project with TensorFlow. Also, this project provides learners with further knowledge about creating and training convolutional neural networks and improves their skills in Tensorflow which helps them in fulfilling their career goals by adding this project to their portfolios.
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1 - 6 of 6 Reviews for TensorFlow for CNNs: Learn and Practice CNNs
By Diego F B H
•Oct 27, 2020
An excellent way to explain this topic 😎
By DALLI P R
•Nov 21, 2020
GOOD
By Sasisrivundavilli
•Nov 21, 2020
GOOD
By kavya c
•Jan 30, 2023
Good explanation and used for basics review. Easy to access files.
By Ghada E
•Dec 1, 2021
Good
By Lasal J
•Apr 19, 2021
The content was there but the explanation is below average. Overall, it wasn't up to my expectations. :(
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