Amazing course, the lecturer breaks makes it very simple and quizzes, assignments were very helpful to ensure your understanding of the content. Hope for future learners you provide code model-answers
I have learnt a lot of tricks with numpy and I believe I have a better understanding of what a NN does. Now it does not look like a black box anymore. I look forward to see what's in the next courses!
By Wei L•
It's a very good course. It illustrates the idea of neural network and deep learning in an intuitive way. I think this time I fully understand the idea and details behind them. Also, the python programming is very friendly. I have used R for years but not so familiar with python. However, folloing the instructions I can do the coding very efficiently. I think i just spent less than 1 week on this course but get 100% score on it. So it's not so challening compared to Machine Learning and PGM. I think PGM is the most difficult one among these courses.
By Dr. H K G•
Dear Prof. Andrew,
It is my pleasure to express gratitude and thankfulness to you and your team.
I am grateful to have you as a mentor in learning AI for everyone, neural networks and deep learning. It was a great journey with you in this learning process. Lectures and assignments made me realize the importance of the ANN and other advance tools in real world applications. The mathematical content behind neural network theory and programming assignments encouraged me to pursue this area in future.
Thank you once again.
Dr.Hari Krishna Gaddam, India
By Nicholas K•
Overall, an excellent course! The material is taught very well. The programming assignments were enjoyable and fairly straightforward. The Jupyter programming notebooks were really cool and fun to work with.
The only criticism I have is that week 1 material was extremely easy, easily doable within a day. Week 2, on the other hand, was quite difficult. I think it was the most difficult week overall because it introduced a huge amount of new concepts and math. After I had a good understanding of week 2 material, the rest of the course was not so bad.
By Rohan S•
This course is a masterpiece. Excellent for beginners and for those who want to refresh their memory. Andrew Ng's way of teaching neural networks with the simplicity of matrix multiplication deserves a standing ovation.
Course Content - 5/5; The material is extremely well structured.
Simplicity - 4/5; though the course requires basic calculus, it shouldn't be a problem
Assignments - 5/5; they were challenging, but it made sure that you grasp the concept completely.
Teaching - 5/5 - Excellent delivery by the master supplemented with easy explanations.
By Christophe T•
Très bonne introduction sur le Deep learning. L’instructeur nous explique les fonctions de base très clairement. C'est ensuite suivi d'une forme de TD ou l'on peut implémenter ces fonctions en python et s'en servir sur des cas concrets.
On ressort en ayant compris.
This is a very good introduction to deep learning. The instructor explains very clearly all the intuitions and the basic fonction of neural network. Then you'll have an assignement where you implement thoose function in python and use them on a real example.
By Aditya V B•
A very beautiful course that introduces us to neural networks and helps gain insight on how neural networks work. One who doesn't know linear Algebra and/or Calculus can also understand the concepts. Programming assignments were good, helped visualize the neural network learning.
The derivations of gradients using Calculus should be proved/solved in an optional video, as it may help people with Calculus background understand the material in depth.
Overall, a very nice course to introduce Neural Networks and Deep Learning, would recommend 10/10.
By Sarmad A•
Very well made. Andrew Ng taught all the core concepts of neural networks very well. Before taking this course, I've watched videos on workings of neural networks. Forward propagation and back propagation always seemed a bit hard to me but Andrew made these concepts very simplified and made me to understand them thoroughly. Extremely satisfied by this course, looking forward to course 2. I would recommend this course to anyone, no prior knowledge of machine learning is required. If you have any interest in this field, I would say just dive in.
By harm l•
Great introduction in neural networks / deep learning. Using Python learning environment is easier than using R which causes me to spend lots of time in installing the right packages in the right versions. Drawback is that i don't have the programming environment ready after finishing this course. It leaves me with knowledge but i have to rebuild the models in a tool i can afford leaving me with lots of overhead things to learn and implement. Overall, good focus on the matter and it's a great surprise to have these results in such an easy way.
By Thejus H R•
Andrew NG really knows his stuff, 10/10 would recommend in a heartbeat! Course is obviously complex, but well worth the time and energy you put into it.
If there is one suggestion that I could give, it is that the grading for the assignments be improved. The grader, in my experience, only gave me either full for each component or a zero. Any change I made in learning rate, etc, did not give me any partial marks.
Other than that, I cannot thank the team behind this, clearly a lot of work went into this seemingly labor of love! Thank you so much.
By Ferenc F P•
Prof. Andrew Ng provides in this course a comprehensive step-by-step instruction to build up your own deep feed-forward neural network (DNN) with backpropagation using only the numpy (library for array manipulations). His approach is from bottom to top starting explaining very basic concepts as building blocks. After those bricks are ready you can easily build your own DNN. It is a great course for beginners wanting to understand how a DNN works. Notebook assignments are moderately hard for a beginner and easy for a programmer with practice.
By Volodymyr B•
Great course! A lot of useful information; definitely worth it, even after taking the into course. I do have two problems:
1) I wish the programming assignments did not help you THAT much. The assignments pretty much tell you what to write. As a contrast, I think that the assignments in the intro course were much more challenging.
2) Although I was able to do the derivation myself, I wish there was optional videos to show the derivation of back-propagation, as I think it is a valuable piece of information for full comprehension of the process.
By Milo C•
I have pass this class.
Except test case of L_model_backward is not match to the teacher, everything is very good.
For the learning strategy, I also have some suggestion for new learner.
If you don't has any experience about machine learning, then Machine Learning class in Coursera by Andrew Ng is good for basic background knowledge. It can help you to quickly understand in simple way. so you can quickly understand the course of Neural Networks and Deep Learning.
Thanks Andrew Ng make everything become simple and good to learn :) Thank you
This Deep Learning course on coursera platform just meets my needs. The instructor of this course is Professor Andrew Ng, who has many years of experience in this field. His Instructional videos and textual materials can help me understand the essence of the theory of deep learning. In addition, after-class quizzes and programming assignments can also greatly increase our practical skills. Therefore I believe this Deep Learning course can help me to possess the basic ability to work in the field of artificial intelligence and deep learning.
By Ryan S•
Very basic concepts are taught, but the material is presented clearly and relatively concisely. The concepts are very accessible and some depth on the mathematics and theory is provided, although not as much as you would get in a graduate level college class. The programming assignments are very good, balancing first-principles implementation with a focus on implementing the most important concepts rather than writing boiler-plate code. This is a good introduction for practitioners and is easily covered in much less time than that allotted.
By Aman R•
Started this course 3 months back, but from past two weeks I sat for around 4 hours per day, to complete this course. The programming assignments may not seem difficult intitally, because Andrew provide the vectorised equations but what really boils down and deepens my understanding was how am I going to use it in my application. How I will build my own image classifier ? When I try to answer such questions then yes it was very very helpful to me. I am still in learning phase, a beginner, so yes course was difficult but it was manageable.
This course is amazing !
I'm so happy that I've completed this beautifully crafted course . The instructor is really good.The explanations and presentations are so clear and easy to grasp.
Before taking up this course,I had a feeling that neural networs are very hard to conceive and implement...but this Course made me realise that anyone with basic knowledge in coding(python) and linear alzebra can easily learn to model Deep Neural Networks.
I thank the instructor Mr.Andrew and Coursera for offering this amazing course. Thank you so much !
By Jairo J P H•
El curso es muy bueno, particularmente estoy muy agradecido con COURSERA, por darme la oportunidad de hacer los cinco cursos de la Especialización en Deep Learning con ayuda economica y permitirme tener acceso a este tipo de capacitacion y certificacion. Muchas Gracias…!
The course is very good, particularly I am very grateful to COURSERA, for giving me the opportunity to do the five courses of the Deep Learning Specialization with financial aid and allowing me to have access to this type of training and certification. Thank you very much!
By Ayush K•
Course if fantastic starters, taking a mathematical approach to the design of NN. Assignments and quizzes are good as well.
However, The format of downloadable course materials need to be improved. It would be nice to see all the documents in one file for a certain Week, instead of downloading files separately. Basically the download format of ML course was much consistent and good for quick referencing.
But nonetheless, 5 stars because above is just my personal preference which has nothing compared to quality and content of the course.
By Reza M•
I wanna thank you for your beautiful and nice website and your great instructors, everything was good but in my opinion if some optional short instructive videos or reading sections about 'dictionary ' and 'tuple' were between videos could be helpful, beside that having some reading parts contain abbreviation of videos that is written by instructors could be useful for student to review in a short time and organized them in their mind would be helpful because details are always forgotten and they're need to be reviewed several time.
By Francisco G A•
Excelente curso introductorio, la curva de aprendizaje es un poco elevada al principio del mismo, pero si tenes una constancia y muchas ganas de aprender es un curso excelente. obviamente es introductorio y segun tengo entendido, todo lo que aprendes a hacer aca, alguien ya lo hizo, pero no esta nada mal aprender las bases matematicas y estadisticas del Machine learning.
TLDR: Buen cruso con buenas bases de matematica y estadistica. Necesitas conocimientos intermediosd e python o algun otro lenguaje de forma seria para engancharlo bien
By Sanjay S S G•
This is truly the best course for those who want to start learning Deep Learning. Our Instructor Andrew Ng , he is amazing!!! . The way he teaches all the concepts are really good , the programming exercises were really helpful.This is a well structured course right from logistic regression to implementing Deep Neural Network.
Overall I really enjoyed learning this course and will continue learning this specialization and apply my knowledge to real world problems. A big thank you to my Instructor Andrew Ng and Thank you Coursera team .
By Sayed A B•
I've been interested in learning NN and ML for a long time and Coursera finally provided this opportunity for me to do it in a timely manner. The time was very limited for such a wide topic, however, I believe they deserve a 5-star for how they managed to benefit such a limited time in a very efficient way. Andrew Ng is one of the best teachers I've had. He's both very knowledgeable, explains the concepts in a simple language, and he's very humble at the same time! Looking forward to getting more courses with him and with Coursera ...
By Andrew E•
Pragmatic presentation of fundamental mechanics of feed forward networks. In particular I appreciated the clean tutorial of the ndarray vectorized implementations.
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.
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.
By Phumlani S•
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.