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Volver a Redes neurales y aprendizaje profundo

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

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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

LV

6 de abr. de 2019

A bit easy (python wise) but maybe that's just a reflection of personal experience / practice. The contest is easy to digest (week to week) and the intuitions are well thought of in their explanation.

AJ

5 de dic. de 2020

This course helped me understand the basics of neural network. After this course I learned to built base neural network model. Looking forward to do the next course of the deeplearning specialization.

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551 - 575 de 10,000 revisiones para Redes neurales y aprendizaje profundo

por Ravi R

21 de sep. de 2020

It's a very good course for beginers in machine learning. Every theoritical aspect of Neural network was explained brilliantly by instructor. Andrew is perfect in his job. But i was little bit disappointed in programming exercises because i don't know much about Python so i didn't understand some of its functions and mainly its imported libraries of Jupyter notebook. There should be one more class or at least a document to explain the libraries and function used in programming exercises.

por Ashwini J

18 de dic. de 2019

Neural Networks and Deep Learning course has been a great learning experience, I had high level idea about how a Neural Network works, having used on structured data before through packages and libraries. But after completing this course and building a neural network from scratch using only numpy library, I now have a good understanding and intuition about why a neural network works. Kudos to Andrew Ng and his team for putting together the content and assignments. This course is helpful.

por Michael F

29 de ago. de 2017

Another excellent course by Andrew Ng. His instruction style is detailed, without getting into the weeds. The lectures provide enough background so that people with (like me) and without detailed linear algebra backgrounds can understand how these algorithms work. There is also plenty of resources available for helping with programming and other details of implementing these strategies. Highly recommended if you want to learn more about neural networks and how to actually implement them.

por Sajal S

22 de ago. de 2020

This is a great course for AI and ML enthusiasts to start learning and making deep learning models. The explanation technique is really good, which makes learning it even more interesting and involved. The programming assignments are intuitive and involving. All in all, if you want to start out in Deep Learning, this is the place for you.

It doesn't matter if you don't know or want to learn the complicated mathematics involved in this field, because Andrew Ng has you covered for that :D

por Mihai L

7 de ene. de 2018

This is another excellent course from Andrew Ng.

After doing his Coursera Octave based initial Machine Learning course I thought I might get up to date to Python /Numpy techniques.

As usual it was excellent. Assignments were not too difficult and you can resubmit multiple times (both quizzes and programming assignments).

Being able to use iPython Notebooks is a great positive point. Installing Python3 + Tensorflow with GPU support took me a long while (just before starting the course).

por Jon M

7 de jul. de 2021

I love how this class continued from the original ML class and switched tools from MATLAB/Octave to Python, pretty effortlessly. I was a little worried at first because of the numpy ways of handling matrices and vectors compared to MATLAB/Octave, but in the end it wasn't that hard to switch gears... (I prefer the .* and ./ notation, but I suppose it's good to know both and not get too attached to one implementation for basically the same thing at a much lower cost point, i.e. FREE!).

por Howard M

22 de abr. de 2021

I had little to no knowledge of Python and numpy and some matrix knowledge before this course, although I did implement Neural Networks years ago in Java with loops but without matrices. This course was great in helping me learn enough Python, numpy and matrix math to actually write a functional Neural Network. The videos were very informative and fairly easy to follow, although it helps to see them twice before the tests. Take some screen shots of the white board for later reference.

por Eunis N

15 de oct. de 2020

This course breaks down deep learning concepts into small enough to digest pieces. It's a very well-structured course and it takes away the fear of calculus and matric calculations. What I liked the most about this course, besides Prof. Andrew Ng, is it gives explanation for the correct answers to practice questions, which not all the courses do. The assignments are very well put together with lots of self-help remarks. I recommend this course to everyone, even the non-mathy learners.

por Bilal K

25 de feb. de 2018

Andrew Ng is an amazing instructor! This is the best explanation of deep learning and neural networks that I have come across. I love how he explains everything from the basics and still covers so much ground. I was intimidated by backward propagation before taking this course. But after going through this course, it seems it is just a fancy name for the chain rule I learned in high school calculus.

Andrew's dedication to helping others learn shows in every lecture. He is a rock star!

por Ram M

5 de feb. de 2018

Very complex concepts have been taught without assuming much mathematical background. Andrew is an extraordinary teacher. I aspire to become as good a teacher as him one day. Also the programming assignments are well designed. The Jupyter notebooks are extremely detailed and are very easy to follow. The interviews with the creators and developers of the field at the end of each week's material are invaluable. Over all, this course and the others in this specialization are outstanding.

por hans m

25 de feb. de 2022

Sincere congratulations to course content creators and specially Andrew Ng. My journey of this first foundational course has been amazing which has left me with the both theoretical (maths part) + implementation from scratch. Just Amazing. I have never been able to gain earlier such a beautiful initution behind Derivatives/gradients. Similarly the way course illustrates of one by one removing loops and build a system of vectorized implementation has been remarkable. Thanks once again

por Lachlan M

22 de ene. de 2020

A superb mathematical introduction to deep learning. Professor Ng and his team ensure that students gain a solid foundation in, and intuition for, the subject.

In my opinion, students will find they are able to focus on the deep-learning algorithms a little more clearly if they are already comfortable with linear algebra and basic Python. Therefore I would recommend taking a course in Python and having a look at basic linear algebra in preparation for this course or in parallel to it.

por Luis H G P

19 de abr. de 2018

Definitely the best introductory course I saw about Deep Learning! :) Andrew is a great 👨‍🏫 lecturer, always emphasising on the theoretical and practical concepts, developing first the right intuition about the topics to further tackle them with the formal approach and exercises in Python. Great methodology as well :) from the simpler to the more complex: it is almost impossible to be lost in this course!:) Thanks a lot Andrew and all the super team of this specialization!!

por Wagner R

27 de dic. de 2019

Very good introduction to machine learning. The basic mathematical foundation is taught and we actually implement a NN from scratch with Numpy. In other courses I made backprop was just rushed, here we have the opportunity of see what is going on and then proceed to abstract it away and use the automatic mechanisms different frameworks offer. Thanks very much Andrew and all the assistant professor for the very 'deep' and well explained coverage of the NN during this specialization.

por Mathew S

6 de abr. de 2019

This class is a great overview of NNs. I have experience programming NNs using TensorFlow, which I learned how to do by following tutorials and using others' open source code. For me, completing this course really fleshed out my understanding and intuition of the internal workings of a neural network. Solutions for the programming assignments are mostly copy-paste-style, but one must think about the equations to do it correctly. Thank you Andrew, and the others behind this course.

por Тесленко С И

23 de mar. de 2019

The course is very, very entertaining. I enjoyed it. I liked your style of presentation of the material and its selection. To be more concrete, that's what I liked most:

+ Practical Assignments

+ Your explanation of hard topics in easy way

+ Deep Learning Legends interviews

Andrew Ng, thank you for the interesting, informative course! I can't stop watching your exciting lectures and solving interesting tasks and quizes. And now I am going to continue my Deep Learning Specialization!

por Baurjan S

17 de ene. de 2018

Very well paced and great in terms of digestibility of the course material. The first course, given you have no issues with the Python syntactics, will help lay the foundation to the principles of deep learning. The bonus of every week is an interview with the stars of deep learning and neural networks. I am lucky I took the course several months after it's been commenced. So there are no errors and it's been a very smooth experience. Looking forward to starting the second course.

por pasquale m

26 de ago. de 2020

i didn't expect an online course to be so well made. i'm an automation engineering student, so i'm interested in detailed maths explanations, and the level of detail of this course is very good. although i would have preferred some more details on some arguments and calculations, that i had to research and compute myself, i understand that this course is not intended strictly for people with strong mathematical background. Congrats to the developers of this course and thank you!!

por Aditya J

22 de jun. de 2020

I tried many other courses but due to the level of mathematics in their i felt like i couldn't do it.This course has helped me a lot for getting the basic ideas of nueral networks and deep learning and the level of mathematics was also a lot better than other courses...Even if you have doubts while doing the course the 4th module will clear it all in the last...So i would suggest to all the people who are thinking to take the first step towards deep learning....Really loved it...

por Ali N

12 de may. de 2020

Best and best before this course I don't know about how these complex computation and how computer can compute all the derivative but now with Grace of Allah and this Course I am now satisfied with this course.. This coursers team and Andrew Ng for giving me this opportunity to become a data and machine engineer and know more about machine and AI and Deep learning. I am thank full to you all. God Bless you keep this charity work for poor students who cannot afford these courses.

por Faraz H

3 de feb. de 2019

Teaches deep learning and neural networks foundations fundamentally and practically very efficiently, quite concisely. Notation standard a little busy but I think optimum. Only thing was the contradicting matrix representations of W and X from lecture notes to the Python notebook medium: Sometimes X has m rows and sometimes it has n_x rows, and sometimes W becomes its transpose, even in the vectorized for all data points cases. Though, in the end, it helps one pay more attention.

por Hari K M

28 de dic. de 2017

Great course. Well taught by Andrew Ng. All you need as prerequisite is a little understanding of Matrix Multiplication, derivatives, specially the chain rule and a little programming experience. If one wants to understand things clearly, I suggest not to miss the optional videos. The interviews with other leaders in the field were informative as well except Geoffrey Hinton's interview which sounded a little high level for a beginner like me. I recommend this course to everyone.

por Abhilasha S

16 de nov. de 2019

I appreciate the work put in making this course so accessile. I loved seeing the equations and math done y Andrew Sir with hand. It helped me pause and do it myself and generate an interest in doing math and linear algera again. Thank you very much. The quiz qns are though not too hard however tricky enough. I liked the course structure too. I do think it would e helpful if you mention pre requisite courses in a specialization or if it's not required. Great course, recommend it.

por Mario G M

27 de abr. de 2019

The quality of the videos could be improved, but the quality of the explanations is excellent. I already knew many of the concepts introduced, but I really appreciate the detailed explanations by the instructor, and the tips acquired from his experience. The evaluation tests are OK, although a bit short to be honest. Practical knowledge is enforced by means of well constructed and very detailed exercises. All in all this is a great course for beginners, I strongly recommend it.

por Leigh L

11 de nov. de 2018

This is an excellent course. I have read tons of the tutorials of deep learning on the other sites. But only this course gives detailed explanation of all the steps. Of course with notebook style step-by-step programming, and Professor Ng's gracious lecture, one will find this course is definitely one of the best Deep Learning Courses available these days. I also very much like Professor Ng's practical suggestions for how to apply Deep Learning principles for real applications.