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Avis et commentaires pour d'étudiants pour Introduction to Deep Learning & Neural Networks with Keras par IBM

733 évaluations
143 avis

À propos du cours

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....

Meilleurs avis


Mar 16, 2020

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


Mar 25, 2020

It is a really good course.\n\nThe labs could have had more for us to do, much of the labs was already implemented.\n\nStill, great introduction to the proposed subjects.

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101 - 125 sur 142 Avis pour Introduction to Deep Learning & Neural Networks with Keras

par Mitchell H

Jun 27, 2020

Great Course!

par Branly F L

May 15, 2020

Very nice..!!

par Sarbjot S M S D

Mar 26, 2020

Really nice!

par Souvik M

Apr 21, 2020


par Saman S

Sep 25, 2019


par said f

Mar 29, 2020


par Krishna H

Apr 29, 2020


par Michael M

Apr 15, 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.

par 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)

par 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.

par Aaqib W S

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.

par Alex S

May 11, 2020

Good course for absolute beginners. Would have liked an extra week or two to 'manually build' some of the key neural network concepts from scratch as in the first week.

par Sameer u

Mar 11, 2020

try to add more case study problems and solve it on lectures so that we can understand how to start (initialize) the coding part when we receive any real world problem.

par 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

par 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

par Ait A O M

Jun 23, 2020

A good introductory course, well suited for beginners looking for general information about neural networks and deep learning, with good practice exercises.

par Lete N

Sep 10, 2020

Good intro to the subject. The instructor could have done examples using other neural networks like RNN and autoencoders. It was a fantastic intro

par Rashmin D

May 14, 2020

It is a good insight for someone to know and understand Deep learning. And exams and projects make sure students learn and practice new concepts.

par Utkarsh

Apr 25, 2020

In-depth concept-analysis is required. Good for people who know the theory and want to learn and revise its implementation in Python.

par Julius M

Jul 06, 2020

This course gives intro to the beginner who start learning the concept of deep learning.... It a good and content are good as well

par Jay P

Oct 05, 2019

Excellent course that is very well done. Final project was super hard.

par mallesh

Oct 08, 2019

Very Good Course to begin, explanations are clear on most of topics

par Vishwanathan C

Apr 14, 2020

Very nice and concise introduction to Keras and Deep Learning.

par Vijander S

Apr 05, 2020

some interdisciplinary data set examples should be included

par jagadeesh k

Apr 27, 2020

excellent course and but need some advanced content