Retour à Réseau de neurones et deep learning

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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....

ST

6 juil. 2018

I think the course explains the underlying concepts well and even if you are already familiar with deep neural networks it's a great complementary course for any pieces you may have missed previously.

NT

17 janv. 2020

Very structured approach to developing a neural network which I believe I can use as foundation for any project regardless its complexity. Thanks professor Andrew Ng and the team for their dedication.

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par Somnath M

•17 mai 2020

I had always wanted, formulae on the research papers to make sense in real world applications. However, as a novice programmer I wasn't been able to put those formulas into code and had to always go through multiple links and videos to make it working which was really a bottleneck as I didn't knew where to start. This course is really comprehensive and well crafted to make one understand the very basics to build a Neural Network and use them any Deep Learning Requirements. If you have a intermediate Python understanding, than no other course can help you create your own Neural Net. Thank You!

par MANUEL A F C

•31 déc. 2019

El primer curso de la especialización no solo te presenta el aprendizaje profundo de forma teórica sino que se ve reforzada con los ejercicios elaborados en el lenguaje python. Terminando con una construcción guiada de una red neuronal de 4 capas y entendiendo cada paso pues son planteados adecuadamente en funciones definidas con anterioridad. Recomiendo ver cada video a detalle y tomar apuntes, así como, practicar uno mismo implentando las funciones y decifrar que es lo que realiza cada línea de código desde un inicio para no perderse después (recomendación: lean los foros). Excelente curso.

par Sahil M

•20 août 2018

Andrew sir introduces the idea of neural networks using a single neuron(logistic regression) and slowly adding complexity — more neurons and layers. By the end of the 4 weeks(course 1), we are introduced to all the core ideas required to build a dense neural network such as cost/loss functions, learning iteratively using gradient descent and vectorized parallel python(numpy) implementations.

Andrew patiently explains the requisite math and programming concepts in a carefully planned order and a well regulated pace suitable for learners who could be rusty in math/coding. I love this course.

par Ye W

•28 oct. 2017

This course serves as a great intro. I saw many comments complaining that the course is a bit too easy. As a stats PhD student, I admit that the technical details in this initial course is trivial, but I feel that I learned a lot of useful things, e.g., vectorization, intuition, etc. In fact, the entire concept of deep neural net is very straightforward, i.e., nothing but a generalized linear model (GLM) from a statistical prospective. I feel what is important is the intuition behind it and how to implement it efficiently in practice. This course covers both aspects in great details, love it!

par GAUTHAM M N

•6 oct. 2020

It is a fantastic course for any one craving about the thrills of programming or math. Anyone without prior knowledge of programming can learn to like this course a lot. Knowing a bit basic math about matrices and calculus kinda makes it more fun, but no compulsorily needed. I am enrolled to all 5 courses in this specialization and will complete all of THEM! Andrew Ng is simply too good :)

P.s: It will get tricky a bit, because the 'what' of deep learning is tough to contemplate. Dont worry too much and just keep learning the 'how'. As time progresses you'll be able to understand it finally.

par Qiongxue S

•14 déc. 2018

This course helps me to understand what is neural network and how would we use the NN and deep learning method to solve the practical problem. This is real science. For the content I have to say that this is the best AI course I have ever had. The related theory and mathematic equations are all clearly explained. Besides I learned a lot from every assignment. The point to build NN is make sure we understand the theory first then the programming part will not be hard. But before learning the course I think we need to have basic knowledge about python. Excellent course! Thank you so much.

par Chris R

•9 sept. 2017

I have already completed Andrew Ng's Stanfor Machine Learning course on Coursera, but the neural network coverage was limited. This course helped me understand the underlying principles of deep learning more completely and I'll be taking all five to earn the specialization. The pace of this course seemed perfect for me having some knowledge of Python, linear algebra, and calculus. This course also helped to refresh older memories and learn new things about Python libraries like numpy. This is an excellent course and has left me very excited about possible applications for deep learning.

par Balwinder C K

•9 nov. 2020

Simply Awesome. I took another course from Andrew Ng (Machine Learning) 4-5 months back but didn't get much idea what's going on. Then i planned to take this deep learning course but before that i did quite to grasp the concepts. I must have watched the other course's video 50 times and must have done 50 small ML examples but that was beginning. This course was breeze as I knew this time the terminology, the concepts and specially what i wanted to learn from the course. It's always good to know underlying concepts as it give you power to debug the not so subtle scenarios.

Thank you Andrew

par Khizr M K

•18 avr. 2020

The course is very good and I found it really easy because I was familiar with python. There are two things which I want to suggest in your courses .

The first thing is you should also teach how to use python libraries for deep learning. This will teach students how to use library in different types of problems.

The second thing which I found was the course was bit easy and it should be made little bit difficult by removing certain hints such as formulae. This will force students to make notes seriously while listening your video lectures and implement formulae in their code on their own.

par Vu L

•20 août 2017

I took the ML matlab version that Prof Ng created, but could not make it because I could not understand the homework problems and the content of the course. Thus, I got out after the fifth week because I could not understand how to do the assignment. However, luckily, right after I got out, he opened this course. It was a relief that I was able to understand everything I did not understand from the previous one, and I was able to do the homework. Therefore, I would suggest this course to everyone who wants to learn AI. Thank you Prof Ng and your dedicated team for this tremendous effort!

par Karl-Andero M

•4 oct. 2020

I really liked the way the python exercises were structured (Jupiter notebook). To let the student only focus on course-specific code, and not implement the entire program from scratch. The only downside to everything I learnt is that I did not develop the intuition for the mathematical formulas of backpropagation. I tried and I watched the optional videos as well but it was quite difficult, because I haven't done calculus in a while. I will rewatch and try to understand that part better. Everything in the course was perfect, will be looking forward to learning the next ones. Thank you!

par Hugo P

•6 déc. 2017

I loved this course and I got much more inspired to pursuit my search in this area hoping that one day I can join this amazing community and get a job in this area!

Thank you very much for your great work: loved the good sequencing of the videos, with very simple and bright intuitions about the more complex math topics, and also enjoyed a lot the Interviews with the gurus/legends of AI and ML!

Congratulations to all that participated and made such a great effort to put up this course available in such a professional format and by such a filantropic price!

Keep on with this outstanding job!

par Sandeep M

•17 févr. 2022

Absolutely stunning course. Professor Andrew Ng really took the effort to tailor the course in such a way that complete newcomers to the field would be able to follow, imbibe and implement the material practically. The explanations on various topics are just amazing and the way advanced topics are introduced gradually on easy-to-understand basics was astonding. And by the time the learnings are implemented on the programming exercises, the concepts are driven hard and everything starts to make sense. I can't thank Professor Andrew Ng and Coursera enough for coming up with this course.

par Yasoda S K

•23 mai 2020

I really enjoyed this course, as far as my knowledge is concerned no other Instructor make this course as understandable than Andrew. Being a person from different background initially I am scared about gaining intuition about the topics but Instructor explains everything in a lucid manner. I am very happy that all the programming assignments are guided in this course, a person with introductory knowledge in python can attempt and gain good grades. I recommend everyone who wants to take this course upon interest can take without hesitation irrespective of their area of study. Thank you

par George Z

•19 mai 2019

The Neural Networks and Deep Learning class from Andrew Ng, deeplearning.ai and Coursera is very well structured and taught. I learned a lot and I am glad I was able to use calculus and Python to better understand what is going on underneath the hood with forward propagation, cost, parameters, backward propagation, predictions and more. Andrew and his team are exceptional instructors. The Deep Learning hero sessions are very motivational and inspiring. I also enjoy Andrew's sessions from Stanford's CS230 online. Looking forward to my next adventure in this Deep Learning Specialization.

par Ivo G

•21 janv. 2021

This course is very complete and takes plenty of time completely covering linear algebra, calculus and programming. If perhaps a bit slow this certainly helps whenever there is something you might not understand at first. I have found the high quality programming assignments to portray exemplary structure in the code and a very accessible way to get some experience working with different machine learning models. The course is setup in such a way that it can be comfortably done alone (haven't really tried the forum). I feel well prepared to get to work on my own deep learning project!

par HEF

•24 mars 2019

Before taking this course I have learned Machine Learning, which is another famous course in Coursera, also taught by Professor Ng. My feeling is that this course is not as intensive as that one, but still I learned so many new stuffs which are extremely useful in my own deep learning projects. Before taking this course, I had zero coding experience in Python and so was really nervous about the programming exercises. However, the exercises are very well organized that I think every one can handle easily. So what I want to say is, don't say you can't do it if you never give it a try.

par Ronak V

•15 oct. 2017

Not sure how other people would fare, but I felt like in order to have a deep understanding of what was actually going on, I needed to go study the calculus and linear algebra behind the material (which I had done previously). I know that probably turns a lot of people off and is why it's somewhat glossed over, but thought I'd just put it out there.

I will say that this course was super helpful with seeing how a theoretical understanding of DL translates into code. The coding exercises were 100/100. So thank you for that! :). Looking forward to the next courses in the specialization!

par Kemal A

•7 déc. 2020

I personally enjoyes this course very much. I think the videos are pretty straight-forward. I really like how every video offers a very brief, yet incredibly detailed recap of what was completed previously and what is about to be reviewed. I'd personally prefer more mathematics, but Andrew provides the equations and optional videos. This enabled me to derive all the equations manually and to compare my results with the ones provided from the course, whereas people less keen on maths were not bothered by this. I would recommend this course to anyone wanting to start neural networks.

par barryhf

•27 mars 2019

It's an honor to be taught by Professor Ng. He's an excellent instructor, and he has very effectively brought this complex material to those of us who are practitioners rather than applied mathematicians.

Perhaps if, like me, you are familiar with the mathematics used in this work, you might find the pace a bit slow. The repetition, and the guided programming exercises, do serve a valuable purpose. By the end, by the final exercise, there is crisp clarity on what all of the components of the neural network are, and how they are utilized.

Thank you, professor, for an excellent course.

par Stanislava F

•31 août 2020

Good balance between theory and practice. The best thing is that everything that you learn during the course you also try in the notebook, right away. So all the formulas and computations become very clear. I have been working with NNs for a couple of years by now and took this course to refresh the knowledge - and surprisingly I have found a couple of things I didn't know before (or have successfully forgotten about). I would also thank Andrew Ng for taking the interviews and sharing these inspiring videos with the students, it's very motivating hearing their stories and advice.

par Mohammad S Q

•19 févr. 2019

First of all the course is designed and taught by AI pioneer Andrew Ng, the fact itself creates no room for any reason for not opting for this course if somebody wants to learn about DL.

Secondly, the approach is ground up, you get a confidence that without knowing or learning complex numerical foundations, you can get intuition of how deep learning works and can very well start applying this into your projects. When you see working model of a deep neural network built from fundamental codes, you feel like doing something and it makes you try harder and wider problems on your own.

par naima v

•27 sept. 2017

The course is very helpful. Andrew Ng has explained all the basics of neural networks. Both theory and programming lessons are very neatly arranged. It helps freshers to learn a lot. Since in programming assignment, the theory and notations needed for that are also explained I could connect everything fast. And I didn't had to code everything in python. It helps people who are not that much expert in python and its an inspiration to learn more in python and other technologies. I express my gratitude towards Coursera and Mr.Andrew Ng for helping for this course. Thanks, Naima Vahab

par Christen

•9 sept. 2017

I had almost zero knowledge about Python language and even less about all the complexity of the internal structure of neural networks (NN). I can imagine how difficult is teaching this sort of witchery to common mortals but Andrew Ng. did a great job on that simplifying and remarking just the practical and important points you require to build a simple NN. It's a clever way to start in the world of deep learning despite of the high price of this course, otherwise it could take ages learning by yourself. I wonder if I will become a kind of wizard when I finish all the 5 courses...

par Matthew P

•7 mars 2022

I've followed similar courses in the past but I can say this seemed to be well structured for the broader audience. Andrew tries not to scare people away with big math and tries to focus on the principles of deep learning. I would highly recommend this course to others that wanted a deeper dive on this subject but are worried they don't have the smarts to do it. This is just challenging enough that you will learn, but not too difficult where you will feel like giving up. It was a good refresher course for me with a slightly different approach than what I've seen in the past.

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