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

4.7
stars
1,465 ratings

About the Course

Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will learn about the different deep learning models and build your first deep learning model using the Keras library. After completing this course, learners will be able to: • Describe what a neural network is, what a deep learning model is, and the difference between them. • Demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines. • Demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks. • Build deep learning models and networks using the Keras library....

Top reviews

MP

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.

AB

Mar 15, 2020

Interesting course. Forward propagation, gradient descent, backward propagation, the vanishing gradient problem, (+ Regression, Classification, and CNN with Keras) explained clearly.

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201 - 225 of 284 Reviews for Introduction to Deep Learning & Neural Networks with Keras

By Sambit S

Sep 1, 2021

very good

By Dr C S Y

Aug 22, 2021

Excellent

By Souvik M

Apr 21, 2020

Excellent

By Saman S

Sep 25, 2019

wonderful

By Ridha O

Feb 11, 2022

good one

By José M

Mar 27, 2023

Good!!

By parisa z

Nov 9, 2022

great

By Francisco M L L

Aug 8, 2022

great

By said f

Mar 29, 2020

super

By Astitva S

Mar 18, 2024

good

By 01fe21bec413

Mar 16, 2024

Good

By mezmur w

Mar 6, 2024

best

By afra a a

Dec 21, 2023

good

By Muhammad M T

Mar 22, 2023

good

By Krishna H

Apr 29, 2020

good

By Rafael G

Nov 3, 2021

Very good course which gives a good introduction to the field. Don't get intimidated by the math you will see and make sure you understand the workflow. Once you do that you will basically repeat it in which one of the neural network types presented at the course. In a negative not, I missed the intructor elaboring how to identity problems that could be approached by applying DL. But I complemented studies on other documents in the internet and that's ok.

By Michael M

Apr 14, 2020

It was a pretty good brief, rapid intro. I frankly was expecting more content on options and explanations, but it covered the very essential basics. The final exercise did ask for students to use tools not gone over in class (a bit of scikit-learn). Since I've used scikit-learn before, this wasn't hard for me, but it may be for a newcomer, and actually isn't needed to meet the goals of the assignment, so I'm not sure why it was there.

By Xiaoer H

Jun 30, 2020

The course contents are not in-depth enough. The server for Jupyter notebook running is way too slow. Besides, the peer review homework is not that good, because some people didn't read through the questions carefully enough, and they misunderstood the questions themselves and could not give fair enough grades to peers. If the final assignment can be made to auto-grading one, it would be much better (we can set the same random seed)

By lonnie

Jun 15, 2021

I have experience of Deep Learning, so I am able to walk through this Lession quickly. The main focus is on Capstone Project, and I have learned something on it. To be honest, this lession is very elementary. I suggest to introduce more Deep Learning models and approachs in this lesson.

By Sander v d O

Mar 14, 2020

This is a great course. The lectures are boiled down to the essence of neural networks using Keras. I give four stars instead of five stars, because the IBM labs environment that the course uses was quite slow and buggy, so I ended up doing the exercises in Google Colab.

By Adriano S

Oct 23, 2020

The Course is basic but interesting. I missed an exercise on backpropagation with the same explanatory level that it had for forward propagation. The last activity needs to be reviewed because it is confusing.

By Deleted A

Jun 1, 2022

Nice overview. The coding exercises could be deeper, and in the second half of the course lose any depth at all. Understandable for such a short course, but still felt like a missed opportunity.

By A Ş

Mar 20, 2020

A good course. Could be better if it was explained how to select the optimal number of layers and nodes. This was not covered and explained anywhere. Overall it was good.

By Rohit S

Feb 21, 2020

I took this course for understanding the TensorFlow properly. Now I am in the situation to understand all the frameworks. Thanks a lot for providing me this free course

By Benhur O J

Oct 10, 2019

Good practical examples for ANN. It could be improved the theoretical part and compare better the architecture of the networks with the algorithms and code for Keras