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Opiniones y comentarios de aprendices correspondientes a Redes neurales y aprendizaje profundo por parte de

113,909 calificaciones
22,517 reseña

Acerca del Curso

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Principales reseñas


1 de sep. de 2019

I highly appreciated the interviews at the end of some weeks. I am currently trying to transition from a research background in Systems/Computational Biology to work professionally in deep learning :)


7 de jul. de 2021

Very informative course by Andrew Ng and team.Teaches everything from the basics and helps you understand difficult topics (as i thought before taking this course) such as Deep Neural Networks easily.

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526 - 550 de 10,000 revisiones para Redes neurales y aprendizaje profundo

por Kiran W

30 de jul. de 2019

Professor Andrew Ng's teaching style is simply amazing! I was able to absorb the material fairly quickly and reinforce my learning with very well structured exercises. I, now, have the confidence that Deep Learning is no rocket science. It is pure mathematics and art at play! If your algebra fundamentals are in place and you are creative, there is no better path to AI than Deep Learning. Believe me, when you start "getting" DL concepts, it quickly grows on you and you are addicted to its philosophy!

por Melissa C

8 de jul. de 2019

So happy I completed the first course in the series of Deep Learning. I got a great foundation for how neural networks work, with good instruction, good illustrations, and plenty of resources. The lab notebooks are particularly well-written, with thoughtful instruction and step-by-step application of what we learn each week. Outputs have "expected" outputs shown below, so you know if you're on the right track or not. Overall very happy with this course. It's a good bit of work, but so worth it.

por Tanmay K

28 de feb. de 2020

An excellent that covers the fundamental required for deep learning. Professor Andrew Ng gives an excellent intuition behind the inner workings of deep learning and practical guides for implementation with the help of the assignments. I found the heroes of machine learning section to be the icing on the cake as it gave a broad overview of the latest developments in the field of deep learning. To anyone who wants to get an insight into this wonderful domain, I would definitely recommend this course.

por Robert G

11 de jun. de 2019

Terrific intro to neural networks! The instruction was very clear on the steps that made up NN/DL algorithms and very easy to follow. I really liked how the programming examples were explicit in what made up the algorithms, and then there were test cases for each section of the code. This made it easy to step-debug through the code, rather than waiting until the code is complete and running into a bug and having to try and trace back through the entire notebook. Thanks for putting this together.

por Glenn B

31 de may. de 2018

Great topic, well organized, and very understandable. Tests and assignments are structured very well and are completely doable.

I get the dynamic aspect of writing the lecture notes in the videos, however the lecture notes should be "cleaned up" in the downloadable files (i.e., typos corrected and typed up). Additionally, the notes written in the video could be written and organized more clearly (e.g., uniform directional flow across the page/screen rather than randomly fit wherever on the page.

por weonseok c

15 de mar. de 2020

Although there are many pre-written codes, I think this course gave a good and easy image how neural net is confirmed and works to a beginner.

Some more things I also wanted are explanations or texts for how to prepare datasets (image data, in this case), and some other usages, not just distinguishing images but sounds or texts and so on too.

But maybe image is most easy example for a person who really don't know well about math or program. I still want to get next courses for further study.

por Subhadip M

25 de oct. de 2019

Extremely helpful course. I got a good and depth knowledge about the Neural Network, Activation Function, Vector and Matrices, Forward and Backward propagation, Parameters and Notation. The main thing I love with this course is the implementation of theory and examples practically on the code. While you are going through the course, I will suggest you to take notes and revise it again and again. Otherwise, you will definitely confuse in many portions of the course. Thanks to Professor Andrew Ng.


9 de jun. de 2020

The course offers indepth knowledge about neural networks from its basic building blocks to large deep learning models. Andrew Ng is definately one of the best teachers and his specialisation in Machine Learning is simply unparalled. The simple explainations and helpful tips throughout the assignments help a lot in establishing confidence while solving them. Highly recommend this course to anyone who wishes to understand the components of a neural network along with larger deep learning models.

por Herment G

6 de may. de 2018

This course is amazing. Andrew is an amazing teacher, you can see that he loves explaining this topic and understands it very well so he know how to put things simply. You may feel lost from time to time but the things that you may hardly comprehend are consistently reminded throughout the course. This gave me a great insight into the field of deep learning and I'm looking forward to learn more about it. I highly recommand this course to anyone who has basic coding knowledge and interest in AI.

por Clemens F

5 de oct. de 2020

The course is excellent. Andrew Ng is an expert on the field and explains everything in good detail. The course reminded me of my econometrics classes. It is always key to get your neck behind the mathematical part in ML/AI to fully understand the effects of your decisions as a data scientist. I love this course for giving me these details.

The Programming assignments where very useful to check your understanding. It took me some time here and there, but I went out with a better understanding.

por Latha M K - P

9 de sep. de 2020

This is my first deep learning course on coursera and I got in depth understanding about various concepts by taking up this course . As I am new to this domain, lectures gave me a clear insight and mathematical background behind deep learning. I enjoyed a lot in coding the concepts learned using Jupiter notebook and its like addiction and I cannot stop until I finish certain assignment exercise. Thanks a lot for this wonderful course and I hope to learn more courses of same caliber in future.

por Michal S

18 de may. de 2019

This was a very enjoyable course! It was very practically oriented, so everyone with some basic knowledge about machine learning, programming and neural networks could complete the course without too much of math background. I know this may seem as a disadvantage as well, but I think having good chance to do cool projects (because the programming assignments are cool) can motivate to further study of presented papers and textbooks well and eventually maybe use the concepts in research or work.

por Marc-Antoine H

2 de ago. de 2020

I checked some courses on other websites and the reviews were not that great. Most often, they don't cover the basics and only explain what Python functions do. This course is awesome. It covers the fundamentals of DL like a college class. This course is particularly appropriate if you have 0 knowledge of AI (and what to learn Python at the same time). Some sections are pretty basic (ex. calculus capsules), but you can skip them. There are 5 courses in the specialization. I highly recommend !

por Pulkit B

14 de oct. de 2020

Great course to get hands on into implementation of neural network. It forces you to learn everything from scratch. Also I liked the notation used, and the clarity with which Andrew Ng explains the concepts.

Just one thing though, if the coding assignments had given much more work to us to figure out and do ourselves that would've been much more challenging. I felt that often the instructions given just before the exercise were pretty much a giveaway in terms of what code needs to be written.

por Jay A

20 de abr. de 2020

Excellent intro course to deep learning. Andrew does a good job of taking students through the basics all the way to the development of a deep neural network. I particularly liked his depiction and explanation of the forward prop, back prop process through the graph. The assignments are challenging and superbly structured such that with some thought and effort you can succeed and actually implement the whole network. I would highly recommend this course to anyone curious about deep learning.

por Mahmoud H

10 de jun. de 2021

I haven't finished the course yet but I admit that Andrew is the best instructor I've met in my life. I've been taking a lot of courses online via different platforms; Coursera, Edx, Udacity and Udemy but this deep learning course with this very very simple explanations helps me a lot grasping main concepts in weights, bias, NN structure and more. I encourage everyone to take this course and learn from the assignments and pay a lot of attention to the material. It'd would definitely differ.

por Hrushikesh V

11 de jun. de 2020

The course is pretty thorough with the theory as well as with the practicals. However, I did feel that I would have understood the implementation procedure much better if there was one more programming assignment per week. Regardless, I was able to follow the course and I'm excited to take the next course in the specialization. I feel like you would be able to follow this course much much easier if you have a good amount of experience with Python and at least a basic understanding of numpy.

por Juan R C C

14 de sep. de 2017

After complete the Machine Learning Course, this one has been more easy to complete than it and, thanks to Python programming, easy to align with other related courses where there are programming assignments.

In addition, it's a pleasure to follow trainings delivered by Andre Ng. His teaching quality is outstanding.

The only "but" is that I missed to use DNN with multiple classification and not only binary classification. Probably it will be covered in next courses into the specialization.

por Maciej B

19 de ago. de 2017

Course is nicely constructed. If you have 2-3 days without other commitments (I didn't) you can finish it very fast including all the - non-required - computations on paper. Coding excersises are well designed although not very demanding. Additional, more complex (bonus) excercises would for a nice add-on to the main course.

The only problem I have with the course is that I must wait 4 weeks for the next step, despite finishing the first stage during the first week. I do not understand why.


3 de jun. de 2021

This is the first Course ever that i took on Coursera and i loved it so much. Andrew is an amazing Teacher and the Programming Assignment are extremely detailed in a way that i have never seen before, even if you didn't quit understand the concepts well in the videos, when you get to the assignments everything starts to unfold. THANK You so much to everyone who contributed in the making of this course and I'm looking forward to start the second Course and the courses of the Specialization.

por Fernando D G

4 de mar. de 2018

I can not express the amazing professor Andrew is. He is capable to explain complex concepts in a way anyone could understand.

I would also like to say that the assignments of this course are amazing. They have taken a lot of time to create the Python notebooks and to match every single line of code with what was showed in the lectures. It's almost impossible not to get confident with Neural Networks after you have completed all of them.

My sincere congratulations to all the teaching staff.

por Joyce G

21 de ene. de 2018

Absolutely wonderful! I have strong math and CS background. I can see this course can be learned by many people from many background.

VERY helpful. I cannot say enough good things about it! Thank you so much!!

The only one thing is that it will be great if the homework assignment deadline can be even more flexible. I work full time and I have a big family. I have been working holidays and weekends to get the course done. It will be nice if the deadlines are more flexible for people like us.

por Nilesh I

29 de oct. de 2017

Awesome course. The teaching style of writing down each small step made it easier for me to understand complicated concepts. Previously I had taken the ML course. Here, the course starts with a simple logistic regression as neural network then 2 layer NN and multiple layer NN. The assignment projects have clear explanation to guide through the assignment projects. The forums are a great help to find cause for errors etc. Thank you Prof. Ng. Looking forward to other courses in this series.

por Devansh K

1 de jul. de 2020

Excellent course! Concepts were explained very clearly and concisely. I really appreciated how much detail the instructor went into. A lot of courses and resources tend to brush over important concepts and just focus on practical applications. It helped a lot to learn the nitty-gritty details that make neural networks work. The assignments were reasonably easy and informative. Only possible improvement for me would be to have more detailed explanations of the calculus behind the networks.

por Pooya D

24 de mar. de 2018

A great introduction to machine learning using neural networks. This course provides a general overview of the mechanism of prediction and optimization of the prediction (gradient decent) using a neural network. The hands-on approach and the minimal lecture videos makes the course interesting.

(I think there might be a way to revolutionize the concept of Discussion Forums to make the learning more interactive with fellow learners but I don't know how so I don't blame the course creators!)