Voltar para Redes neurais e aprendizagem profunda

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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....

SS

26 de nov de 2017

Fantastic introduction to deep NNs starting from the shallow case of logistic regression and generalizing across multiple layers. The material is very well structured and Dr. Ng is an amazing teacher.

MZ

12 de set de 2018

This course is really great.The lectures are really easy to understand and grasp.The assignment instructions are really helpful and one does not need to know python before hand to complete the course.

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por Giovanni

•4 de fev 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 mai 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 Thomas M

•27 de set 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 set 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 dez 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 dez 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 out 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 out 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 Meeran M

•14 de out de 2022

I am doing this Deep Learning Specialization. Kick started the week 1 by auditing the course. By the end of week 1 I gained a lot of confidence and I paid for the course. Andrew NG made the deep learning easier by his style of teaching every single complex derivatives in a detailed and easy to understandable way. I would recommend learners to watch the videos atleast twice to register the steps and formula involved in this course and must takes proper notes with pen and paper. The more you practice the easier it gets.

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 jan 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 out 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 dez 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 set 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

por Ram S

•11 de set de 2017

Superb course. Not only is Professor Andrew Ng a colossal scholar, but he is a brilliant teacher and knows how to get complex deep learning concepts to anyone who has basic math (algebra and calculus) skills. He also brings out the insight and intuition into why deep learning works. And the course is so very well designed and the programming exercises so thoroughly and precisely crafted. I enjoyed every minute of doing this first course in the series and look forward to the remaining courses in the series. Cheers Ram

por Joe M

•7 de jun de 2019

Great course, the material was clearly presented with alternating between high level and actual coding implementations. The interviews with practitioners were really insightful. More references to some of the background on things like linear algebra or other math topics would be great. Some tricky parts of the programming assignments, despite much of the code laid out for you. They definitely helped me -- an experienced coder who hasn't looked at that much math in a long time -- on some of the higher level concepts.

por 罗广地

•13 de abr de 2019

Deeply sighed by Andrew Ng, learning this course is a great way to enjoy the process. Among them, the check-in benefits of programming settings can consolidate and enhance understanding of what you have learned. The program in week4, when I was not learning, I wanted to write a neural network that could configure the number of layers arbitrarily. Under the leadership of Ng God, the work is very comfortable. This program can also be ported in other projects in the future. outstanding. I really like the series. thank.

por Niall O

•7 de mar de 2019

I loved this course. The course builds the conceptual understanding and maths to build a functioning Neural Network from scratch using just python and numpy. I would recommend people wishing to take this course first take Andrew Ngs Machine Learning course on coursera and pay particular attention to the first 3-4 lectures that build up your visual intuition for ML and Logistic Regression. Now that I know the basics I'm looking forward to completing the remaining courses on the specialisation to improve my knowledge.

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