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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

NL

3 de oct. de 2020

This course helps me to understand the basic concept of Deep Learning. However I think this course should include at least 1 week (or 2-3 videos) about math so learners can have a better understanding

AK

13 de may. de 2020

One of the best courses I have taken so far. The instructor has been very clear and precise throughout the course. The homework section is also designed in such a way that it helps the student learn .

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601 - 625 de 10,000 revisiones para Redes neurales y aprendizaje profundo

por Abhinav P Y

10 de jul. de 2019

Prof. Andrew Ng has done a great job by explaining the mathematics behind the workings of a neural network, and the programming exercises using python have been very well organized. This course definitely serves as an amazing background to other advanced courses in deep learning. I have thoroughly enjoyed and learnt a significant amount throughout the course. This course might also serve as a great refresher to those who haven't been in touch with the mathematics behind

por Tiberiu B

28 de ago. de 2018

The course is excellent. The programming assignments are well balanced.

They take you from basic python and numpy and they gradually increase complexity until you get two things: (a) good knowledge of feed-forward neural architectures, hyper-parameters, non-linearities, back-propagation, derivatives etc. (basically ML stuff) and (b) a principled way to code your models, which allows you to quickly switch to more complex network structures with minimal effort.

Thank you!

por Benny P

20 de feb. de 2018

This is an excellent course for anyone who wants to know more about neural networks and gets some update of the latest developments since what was taught in Stanford's ML course. As in the ML course, prof Ng speciality is to make difficult subject so easy to learn and so accessible for everyone. Compared to other NN/DL courses/books, this course is relatively easy, and it's good for getting the overview about the subjects before jumping into more advanced NN/DL courses.

por Baohe Z

3 de sep. de 2017

Skilfully avoid those complex math problems, Andrew gives us beginner a overview about Deep learning and its application. Also the way he picks up to teach us is very fascinating. Almost hand by hand teach us writing code, how to organize your coding structure, and step by step follow his teaching to build your own neural network. I can't say it's very technical dictionary designed for those old master. But if you're interested in AI, this course should be a good start.

por Vijay M

15 de ago. de 2022

I​t is a really great course if someone wants to dive into the field of deep learning. This course provides sufficient introduction to theory of Neural Networks. Assignments are little bit easy, they only include implementaton of equations in python.

I​t would have been great if there was at least one assignment where students implement deep neural network from the scratch without help of any source code provided from course staff.

T​hank You for such an amazing course!

por Vadim T

11 de jun. de 2020

I like the idea of building NNs from scratch as I believe everyone working in ML should understand basics such as matrix dimensions matching and back prop calculus.

Andrew's way of explaining ideas is very clear and concise as always.

Programming assignments are relatively simple as varieties of hints are being provided. Nonetheless, they still make me think algorithmically and analyse the procedures implemented.

Looking forward to other courses in this Specialization.

por Mihai-Cristian O

28 de jun. de 2021

I honestly think that auditing the course provided me with a PROPER trial of the whole course. I would have liked it to be a bit more challenging (on par with University courses), with overall, it is a more than appropriate specialisation to consider.

I actually ended up purchasing a subscription for a month to gain the certificate :) ! I do not know how I am going to fair against the other courses in this specialisation, but I have been pleasantly surprised so far! :D

por Shumin L

4 de feb. de 2021

I love this class and Andrew Ng. I think Ng's class is very efficiency for a beginner to Deep learning. Because An usually talks in a gentle and slow way(which I prefer ;) ), this course is even useful for non-English native speakers as they can learn English in this class too.

Also, the programming assignment is very helpful for me to get a deep understanding of what Ng had taught in the vedio.

In a word, I love this course as it give me a key to deep learning and AI.

por Mohammad A P A

9 de sep. de 2019

Everything was great, Except for two things! First, the grading system didn't work well, sometimes it just showed me my older grades or it wasn't aware that I have finished the specific subject. Second, the matching names of the variables helped me a lot on writing the codes, I guess with different names in different places I would have to think more to do the computer assignments. Anyway, had a great time and experience. Thank you for all your passion on this course

por Vihanga J

18 de mar. de 2021

This course was extremely helpful to gain a basic understanding of neural networks. The lessons are very clear and easy to understand, and they provide all the guidance needed to successfully complete the assignments and quizzes. I'm looking forward to further enhance my knowledge by completing the remaining courses of this specialization as well. My heartfelt thanks go to the instructors, DeepLearning.AI, and Coursera for providing this amazing learning opportunity.

por Parth P

10 de may. de 2020

I have a great experience learning this course. As stated by Prof. Andrew NG, I came to know new things about the algorithms. I was familiar with the algorithms but still had an opportunity to learn new things.

The explanation about the code was extremely good. Assignments are really very well defined and worth learning. I am very grateful to Coursera as well for providing such an extravagant opportunity to the learners.

Thanks a ton for the course and financial-aid.

por Duncan K M

27 de sep. de 2017

This is an awesome course, Ng covers all the material thoroughly. He provides enough guidance and structure to both make the assignments accessible and allow students to build their own tools from scratch. I've been working on doing each assignment in R on my own and building the tools to make up for the differences in how things are handled in Python packages vs R. I have definitely learned more here than in other University courses that went over these subjects.

por Andrew W

18 de ene. de 2021

Excellent overview of the basics of neural networks! Andrew provides good intuition of the maths and explains the ideas very clearly, making them easy to follow. The only minor criticism I would have is that I would have liked a little bit less guidance from the jupyter notebooks when implementing the code in our assignments. At the same time, I recognise the course needs to cater to learners of many different backgrounds, thus I have not removed any stars for this.

por isa t

27 de dic. de 2017

Andrew Ng and his team showed their teaching abilities again. This course teaches the fundamentals of Neural Networks and Deep Learning. The lectures are very clear and comprehensive. I really liked 'from scratch' approach of the assignments. Assignments are not so difficult but very instructive. Jupyter notebook is very easy to use. The test examples after each function are also very useful because I did not have to check all the code for a simple function mistake.

por Ori M

22 de oct. de 2017

Thank you!

It was a great course. The only thing that bothered me slightly is that the coding assignments were so "closed" and didn't let me code freely. In addition, I didn't like the "bottom up" approach, i.e - first coding the basic tools and finally code the whole picture algorithm. I understand it is not easy to take the "top down" approach in an online course like that and appreciate the approach you took.

Thanks again, see you in the next specialization course!

por Manthan P

29 de jun. de 2020

Love Andrew's approach of keeping things simple. If you want to understand the basics of Deep Learning and get good INTUITIONS of how things work, this is it!! I had already experimented with Keras in my past but after taking this course I realize I should have done this earlier!! It is quite important to understand what the libraries are actually doing. That is when you get a good sense of what you are actually doing and most importantly, you ENJOY working on it!!

por Ian L J

21 de may. de 2019

Fantastic introduction! Andrew really explains this well, in-depth and in such a friendly, encouraging manner. Regarding the programming exercises: there is a fine balance between guiding the student in the right direction with hints and the student encountering frustration if the answer cannot be arrived at within a given time-frame; I think these exercises were well-balanced in that respect. A thumbs up and 5 stars for this one -- I thoroughly enjoyed the course!

por Massimo F

18 de ago. de 2018

very good intro to deep neural networks; some topics are perhaps treated a bit too quickly and without much details on the underlying mathematics, but the core concepts are there and very well explained.

The coding exercises are a bit too simple, almost spoon-fed. On the other hand by completing them one gets a collection of working routines for NN that can be reused in other projects.

I only audited the course, so I cannot comment on the graded exercises and quizzes

por Fabian R

13 de mar. de 2018

I really liked the course. I already took the machine learning (ML) class by Andrew Ng and must say that I do like this one even more. The programming assignments are very helpful and using Jupyter Notebook is very convenient and much better compared to the textfiles in the ML class.

Would definetely recommend the course! But one has to be aware that it can be frustrating when one gets stuck here -->I highly recommend the Discussion Forums .

Thank you for the course!

por Tasnim M

14 de ago. de 2017

This is a great course. Prof. Andrew Ng gave a lot of effort to design the course. Rather than diving into neural network directly, he build the intuition from logistic regression - that's really impressive. I am really amazed by his teaching methodology.

And the programming assignments are too awesome. In theory, he build the mathematical foundations which are implemented in the assignments. Learned a lot from this course.

Hats off to Prof. Andrew Ng and the team.

por Evans O

4 de ago. de 2022

In this course, Andrew takes you through the essential skills needed to build a neural network architecture with only one output. This is the right way to start, and I liked the hints provided in the exercise notebooks to guide the thoughts of students not only to solve the exercises but to understand the content of the lectures. I will definitely recommend this course to anyone who wants to start learning deep learning and also building deep neural architectures.

por Raaja A T

30 de jul. de 2020

This course was Awesome, and thanks to Mr.Andrew NG for teaching the course in much simpler and in an understandable way. It is really a pleasure to have taken and finish this course as it gave a good image on Deep Leaning and Neural Networks. Quizzes after each week's module was very entertaining, but, some programming exercises were quite difficult to get through, initially, but after getting more insight on the week's content and lectures, we could get it done.

por Eileen C M

12 de abr. de 2021

I was very impressed by how well organized this course was. The information was well-chopped up and presented in bites that were easy to digest. (FYI: I know a LOT of calculus.) The lab assignments especially were well designed, where we only had to write the relevant lines of code to complement the main structure that was already created. This allows the student to focus only on the material learnt in the course and not all of the intricacies of Python, etc.

por Edmund T T

10 de feb. de 2021

I think every ML enthusiast, must consider taking this class, a lot of good explanation that can be considered looking into for research topics. Hey ! anyone aiming to be ML-specialist needs to start from here, I bet you, you won't regret it. And for you, students out there, who are quite lost in ML class should consider this wonderful well structured and explain ML concept to the basic level. I rest my case. rat-ta-ta-ta (Million gunshot salute), to Andrew Ng.

por Phan C N

21 de feb. de 2020

A very easy to understand course for beginner and even people who familiar with machine learning. I used AI before, but want to go back to study more about the basic, and this course help me to reinforce my foundation in machine learning.

A lot of mathematics problem is explained in a way that easy to understand. Exercises are built to help you understand the concept. Lessons are much easier to understand than other online lecture (or even lecture at university)