Volver a Redes neurales y aprendizaje profundo

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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....

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.

AG

6 de mar. de 2019

I understand all those thing which you have discussed in this course and I also like the way first tell story of concet and assign assignment. Now I fall in love with neural network and deep learning.

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por Andrew E

•10 de sep. de 2017

Pros:

Pragmatic presentation of fundamental mechanics of feed forward networks. In particular I appreciated the clean tutorial of the ndarray vectorized implementations.

Cons:

The one feedback I would give is that the coding exercises had a lot of hand-holding. For a specific suggestion: some of the "asserts" used for checking correctness give away the answer. I suggest refactoring the checks to be private methods invoked in the notebook but implemented server-side. That way they can be inserted in the code without leaking the solution.

por Ivan

•10 de mar. de 2019

Amazing stuff. I've been looking for a good introduction to Neural Networks, looked through a lot of tutorials and blog posts (of which there are multitudes these days, since Deep Learning is all the rage now) which only confused me more, and finally decided to take on a full-blown course. Turns out, once somebody like Andrew Ng explains this stuff, it's no longer mysterious and convoluted.

Note, that it's better if you're at least familiar with matrices and vectors from calculus before taking this course since NN are all about it.

por phumlani s

•1 de feb. de 2019

Excellent course, good balance between theory and practice. The teacher thoroughly explains all the elements of deep learning before you're given the programming assignments. He gives you both the theory and the brief overview of how it all works. The programming assignments are designed so that you only focus on the "neural networks and deep learning elements", you won't have to worry about programming environments or what libraries to use, which saves a lot of time and gets you going on the most important aspects of the course.

por Валиев И

•24 de jun. de 2018

Wonderful course.At the beginning it even seems to be too simplified (course team explains everything and structures the code for you). But this is just an illusion. Closer to the last week you start understanding that multiple reherasing of the basic neural network concepts is key for conscious understanding. And that structured code is wonderful (in Russia it's not practiced =(( ). Separate thanks for backpropagation explanation with computation graph. That was very helpful.I'll definitely recommend this course to other people.

por Pritam D

•13 de mar. de 2020

This was a grate learning experience,I have not seen a single tutorial that has covered building Neural Network from scratch like this one.Perfect combination of code and the underlying concepts have been explained in a very intuitive manner.The additional part "Heroes of Deep Learning " was very much inspiring. The discussion forum was great I've learnt a few additional things from there. Thank you sir for providing such a quality course,I'm very much satisfied with the quality of content and as well as the method of teaching.

por Giovanni

•4 de feb. de 2019

As someone with a strong background in mathematics and a good programming skills, I found the course level rather "basic" and I could quickly absorb all the lecture's material. I found the materials extremely interesting and well organized. The assignments, though rather straightforward (implementing what has been explained, nothing more) were difficult enough to made me feel I was "building" something. And then, the possibility to experiment and play with the code was also great. Overall, a very good corse, thank you professor!

por Mingchang L

•21 de may. de 2018

Sometimes it's difficult to connect to the server when doing the programming exercises. The course is well structured. However, the programming exercises can sometimes be confusing because there are quite a few "helper" functions in the deep learning algorithm. Students may need to consistently refer back to the help functions defined earlier to implement the final learning algorithm. Overall, it'a great introductory course. Andrew has given very clear explanations and useful pointers when implementing deep learning in practice.

por Yawar A

•3 de nov. de 2018

It was a nice experience with a such a experienced and well knowledge supervisor. Who just started right from the beginning and then distributed the course in easy chunks so that all the content remain understandable to every type of learner. I thanks specially to Higher Education Commission of Pakistan who has offered such a splendid course to increase our domain knowledge and also thankful to supervisor and coursera team who have done such a excellent offer to spread the knowledge by using most modern techniques of learning.

por Tom M

•27 de sep. de 2018

This course is my first in Deep Learning and has been very interesting for me. The inclusion of the notebooks and grading are a very useful touch. Andrew does a good job trying to abstract away the complexity of Deep Learning, but it still does require some understanding of programming (python), calculus (mostly derivatives), and matrices/linear algebra. For someone new like myself, I find that I often need to pause the video, take notes, and also just rewatch lectures multiple times before I start to understand the material.

por Glen D

•22 de sep. de 2018

NN&DL is much shorter and much easier than Dr. Ng's original ML course, and the material overlaps a lot. I finished the course in 2 days (not 4 weeks). As always, Dr. Ng's explanations are clear, and the material is beautifully organized. I felt the answers to the assignments were a little too easy. Not really a lot of thinking required. The interviews with the "heroes" of Deep Learning were fantastic. Their ideas about the future were very inspirational. I am looking forward to the next course in the specialization.

por Muhammad T B

•11 de nov. de 2019

It was a wonderful course to get started with Artificial Intelligence and Machine learning.Those concepts of forward ,backward propogation, relu and sigmoid function was really new and helpful to get insight of what happens behind the scenes of machine learning algorithms many concepts were new and typical but Sir Andrew did a great effort and explained them in a way that everyone can understand it. I highly recommend as a student to take this course and challenge your skills with what you can do to contribute in AI world.

por Sai H

•6 de dic. de 2018

This course is a very good kick-start for learners in deep learning. Prof. Andrew Ng explanation covered most of the details required for building neural nets and the programming assignments gave a clear idea on working of the neural nets. I got stuck at some point in programming assignments, later I completed it successfully before the course ends. I experienced the same excitement from starting till the end of the course. Thanking coursera for also providing financial aid. Looking forward to complete this specialisation.

por Yongjun L

•6 de dic. de 2019

This was such a helpful lecture. It is very well organized, and great for all learners with various backgrounds. I was very surprised with the diversity of people who take this course. The discussion forum on this course is absolutely fantastic. You can find all the possible problems/questions you might run into, and they are all answered by numerous mentors on this course. I highly recommend this course to anyone that are looking forward to start deep learning/ai. I am actually anxious to start the next course materials.

por Alex D

•31 de oct. de 2019

I loved that this course married both a 'top-down' and 'bottom-up' approach. I started my deep learning journey with FastAI (not to slight Jeremy, he is a phenomenal teacher and I understand the logic behind his teaching style), however was craving some 'lower-level' concepts out of part 1 WITH math notation. I thought this course did a great job of finding a medium between these ideas: starting with something lower level + math notation, but also providing practical notebooks and algos with working model implementations.

por Harshit P

•29 de oct. de 2017

The main take away for me from this course is to learn how to systematically denote various quantities involved in deep-learning such that they can be recognized later without any confusion (e.g. dW is gradient of cost with respect to W and so on..) and to learn how to structure a code to implement any deep neural network. Also, from data analytics perspective, I learnt about the limited representational capabilities of simple models like logistic regression and why deep networks tend to work better than shallower models.

por Anish P

•23 de mar. de 2019

It's a very good beginner level course on the basics of deep learning. Back propagation has been explained very well. The intuition and derivations of mathematical formulae are not too deep but can definitely be researched in text books. The assignments involve a lot of hand holding which is fine. One can attempt the assignment all over again in their own Jupyter notebook but this time write the entire code from scratch (referring to the assignments only when needed). The assignments also teach the best coding practices.

por CLAUDIO A

•4 de jul. de 2019

The course is really well structured, Andrew's lectures are really very easy to understand and on top of that, he also goes over certain topics more than once so that reinforces your learning . The assignments and quizzes are very well organized so you should not have any issues or ambiguities when submitting them. I was interested in the Neural networks topic since being an "old school" grad in Computer Science , at the time this field was not even in the syllabus of the universities so this certainly filled the gap !

por Vikas

•24 de jun. de 2020

Loved the course. Big Big thanks to Andrew Ng for teaching the concepts of Neural Networks right from scratch with the great explanation and step by step deriving the equations and explaining each n every bit. I have taken other courses on Machine Learning and Neural Networks but no one has taught the concepts like this. You must take this course if you want to learn the concepts of Neural Networks. The python exercises are also very informative and helps you learning and building the whole neural network from scratch.

por Mr.zhao

•18 de mar. de 2019

Thanks for Coursera for make this online education, letting more people to get to learn thing they interested. Professor Andrew Ng make this course very easy to understand, although you have a poor knowledge about the math. Besides the assignment was much easier than I thought, what you need to finish is the some few core code, and the whole structure was finishe to guide to finishe the whole project, after several testing and reviewing, you would finish it by yourself and have a better understanding about this course.

por 杨建文

•10 de ene. de 2018

The course starts from the basic structure, which make it very easy to understand. But very good courses can also have some small shortcomings:1.Lectures slides is not provided 2.It aims at very large population, so those who want to do research may need to dig deeper themselves(I suggest learners focus not only on the code you are required write, but also the whole network) 3.The programming exercise is a little bit repetitive. But overall, this course is still very helpful and efficient for beginners, thanks Prof.Ng!

por Nathan D

•11 de ago. de 2020

Really great way to learn about neural networks for both beginners as well as intermediates. The programming exercise with partially per-written code is very helpful and helps save a lot of time in coding so that students can focus on the important parts of the exercise, something which many online courses do not do, A big thanks to Prof. Andrew Ng for incorporating the heros of deep learning as an optional part of the course which helps students get motivated and understand where deep learning processes can be used.

por Joao N

•20 de oct. de 2019

The theory was laid down nice and easily even when maths started to get involved. The theory also tied up quite well into the practical assignments. One think that could be improved is the quizzes at the end of each video. I quite enjoyed them on Week1 and they do not seem to be consistent throughout the remaining weeks. Even having quizzes where the answers might not have been mentioned in class but they can be easily found with a bit of research (as long as the reading is worth it) could be an interesting addition.

por ZIQI Z

•12 de ago. de 2018

I would like to rate this course with a mark of 4.5/5 (although I rated it with all the stars). Overall, the course setting and content are great. Andrew does tell everything intuitively! It would be a great course for anyone who has certain background knowledge about neural network and deep learning.

However, the only thing that I would probably suggest is that maybe we can make the programming assignment more challenging.

But anyway, this is a wonderful course! I am looking forward to stepping into the next course!

por Max

•31 de dic. de 2017

A very nice introduction to neural networks. The build-up form logistic regression to a deep network was executed very well, and allowed me to attain a good initial understanding of ANN's. My feedback would be to include a bit more optional video's/written materials on the derivation of all the formula's (especially vectorized back propagation). Having some calculus experience I managed to do the derivations myself, but I think it would be nice if the derivation is explained somewhere clearly in some sort of appendix

por Ashwin A

•29 de sep. de 2017

Amazing course. It was well paced and structured. The programming assignments were fun and intuitive. It would have been nice to have had a few more optional ungraded programming assignments though so we could try our luck with different kinds of problems.

I especially enjoyed Professor Ng's explanation of forward and backward propagation in computation graphs . It was very intuitive.

It would also be nice if the lectures could have links to some of the literature behind the algorithms and concepts discussed in them

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