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Learner Reviews & Feedback for Introduction to Deep Learning & Neural Networks with Keras by IBM

4.7

stars

2,028 ratings

About the Course

This course introduces deep learning and neural networks with the Keras library. In this course, you’ll be equipped with foundational knowledge and practical skills to build and evaluate deep learning models. You’ll begin this course by gaining foundational knowledge of neural networks, including forward and backpropagation, gradient descent, and activation functions. You will explore the challenges of deep network training, such as the vanishing gradient problem, and learn how to overcome them using techniques like careful activation function selection. The hands-on labs in this course allow you to build regression and classification models, dive into advanced architectures, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and autoencoders, and utilize pretrained models for enhanced performance. The course culminates in a final project where you’ll apply what you’ve learned to create a model that classifies images and generates captions. By the end of the course, you’ll be able to design, implement, and evaluate a variety of deep learning models and be prepared to take your next steps in the field of machine learning....

Top reviews

Jun 29, 2020

Such a wonderful and high tech course in the world and it is provided by ibm and coursera.Thank you ibm and coursera for such a opportunity.I'm glad and proud to be a part of this organization.

Jun 30, 2022

Excellent introduction to the mechanics of Neural Networks in general, and the Keras application specifically. Alec is an outstanding teacher, I always appreciate his knowledge and enthusiasm.

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By Dr C S Y

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Aug 22, 2021

Excellent

By Souvik M

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Apr 21, 2020

Excellent

By Saman S

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Sep 25, 2019

wonderful

By Mohamed

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Feb 11, 2025

its good

By Ridha O

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Feb 11, 2022

good one

By Simha C

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Aug 26, 2024

Awesome

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May 7, 2025

useful

By José M

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Mar 27, 2023

Good!!

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Jul 12, 2025

good!

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Nov 9, 2022

great

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Aug 8, 2022

great

By said f

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Mar 29, 2020

super

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Nov 21, 2025

nice

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Aug 31, 2025

good

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Aug 30, 2025

good

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Apr 29, 2025

Good

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Apr 25, 2025

good

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Apr 19, 2025

Good

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Mar 28, 2025

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Aug 15, 2024

good

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May 22, 2024

good

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Mar 18, 2024

good

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Mar 16, 2024

Good

By mezmur w

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Mar 6, 2024

best

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Dec 21, 2023

good