Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.
Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course
by Pawan S S•
One of the rare courses teaching about structured hyperparameter tuning. All the subject matter are well taught and the flow of the module is very easy to follow and understand. Together with the programming assignments, I was able to quickly grab the essentials. I highly recommend this course for any deep learning enthusiast.
by Jeroen M•
Great course, a few rough edges in the exercises and I also feel the exercise comments give away a bit too much (would be better if the student needed to figure out things by himself a little more). But these are minor details, I've learned a great deal in an amazingly short span of time, from one of the top minds in AI today!
by Jeff R•
I appreciate the large amount of time that has gone into preparing this course. I note that there are a large number of corrections in the errata forum that have not been reviewed by staff. In particular there are some obvious errors in the programming assignments that could easily be corrected with a small investment in time.
by Pranshu A•
Awesome, Amazing, Best, Fabulous course. Learnt a lot about Hyperparameter tuning and atlast got an intro about tensorflow framework which i wanted to start learning but earlier afraid from it's complexity which is explained so good in this course. Best course for Tensorflow Intro and Hyperparameter tuning in Neural Networks.
by Murat T•
Topics cut in to sections are well defined and so clear. Programming assignments definitely gives you hands on experience. Also, math is demystified that you track with high school math. If you used framework like Keras and you want to know why and when you need to use that function,parameter etc., you would love this course.
by Gilles D•
Eventually a clear and definitive explanation about Network initialization, regularization and optimization. Good insight share on hyper-parameters prioritization.
We learn the how and why and suddenly, it all becomes a little bit less mysterious. It is all clearly explained in a very accessible way.
Great value for my needs
by Xuefeng P•
This course really gives you a fundamental and practical ideas about the hyper-parameters of DNN, and the way of tuning them. The part I liked most is the last programming assignment ---- play with Tensorflow!!! The assignment walks you through Tensorflow structure and basics in a very organized fashion.
by Akash K•
Really enjoyed the course as it covered a lot of regularization and optimization techniques in depth. Programming assignments are really easy as it needed to write only few lines of code but serves its purpose and enforces the learnings from lectures. Highly recommended to get the exposure before starting your own journey.
by Ali n•
Best course for learning Hyper parameter tuning, Regularization and Optimization topics further more the batch and other various optimization algos like momentum, Adam, Batch norm etc are much easier here. Please have a look on ground reality too, Take quiz before staring any course that this candidate is suitable or not
by Mihai L•
This course is also interesting. The art of tuning hyper parameters and other optimization techniques are very interesting and nicely explained.
The introduction to Tensorflow and assignment is also interesting.Overall the difficulty is not high but the concepts are really powerful and important ,most scaffollding is done
by Ferry v A•
This course provides a good overview of the optimalization techniques for neural networks. It refers to both the basics by providing an explanation of moving averages, and the advanced by providing references to academic literature. Finally, it provides the rules of thumb that a practitioner needs when iterating models.
by Vlad M•
The course part is overall good.
The last assignment can be improved in two key ways:
The comment # Z3 = np.dot(W3,Z2) + b3 should be # Z3 = np.dot(W3,A2) + b3 - figured this out by myself without help from forums. :)
Also, the Adam optimization is not very apparent in the instructions - searched in the forums for issues.
by Adam F•
I completed the entire specialization and having nothing but good things to say. Highly recommend it! Lectures are engaging, and Andrew does a fantastic job explaining some very complex topics. Programming assignments are challenging in a good way. You’ll really feel like you’ve learned a lot by the time you’re done.
by Evandro R•
Another wonderful course of this amazing specialization. I could say a lot of things, maybe even pages on how Professor Andrew it's the right person to teach you about Deep Learning but I'll shorten in this review and recommend the whole specialization for you! It's worthy and there's a lot of knowledge to be shared!
by Brad M•
In my deep learning classes in academia, hyperparameter tuning was always "hand-waved" away - my questions were always deflected, or put off. This class answered every one of my questions, and made me more confident I'd be able to implement a DL system in industry, and be satisfied with the results. Very good course!
by Zeinab B•
This course will cover everything you need regarding your neural network performance. I always had questions on why and when you use Adam, SGD, etc. and after this course, I have a much better understanding of how to choose hyperparameters and optimization methods. I highly recommend this course to ML practitioners.
by Toby K•
I am working through the DL specialisation. Consistently good teaching style and the programming assignments are suitably pitched for getting the learner to pick up methods quickly e.g. Tensorflow syntax for self-application later. Good course and looking forward to the next in the series. Well done Andrew and team.
by Ankur T•
word is not sufficient signup and experience it. For a deep learning beginner who already have math background can easily understand concept behind it but for implementation you need to refer extra materials on internet and book too. Andrew Ng explain only concept and recipe but for practice you will struggle hard.
by Nhut D•
Great course! Help understand the mathematics and intuition behind hyperparameters and regularization methods. I feel the material is well-prepared. However, the last lab is quite confusing because I think we are not prepared enough about tensorflow fundamental throughout the course to really apply it in practice
by afshin m•
This course is continuation and a requirement of the first course. Really like the learning style of how first course and the first 2 weeks of the second course taught neural networks by doing all the math and calculations manually and finally introduced Tensorflow with parallels of what was taught in the class.
This is another excellent course in this specialization. I enjoyed the programming assignments. The instructions, tips made Tensor flow coding section to be easy . However, few blocks consumed more than few hours, due to placeholders. logic and the TF documentation is overwhelming. I am proceeding to next course.
by Wei L•
This course is harder than the previous one. It teaches more details of tuning parameters and optimization in deep learning. In the end it also teaches tensorflow which is really helpful. It's like a programming course, nerally all the commands have been already provided, so it's not hard to get the code correct.
by Muhammad T•
As usual, Andrew is a great instructor. He taught very complex concepts in very simple language and used notations that were easy to understand and were consistent throughout the length of the course. WOULD DEFINITELY RECOMMEND. I am hoping to complete the specialization in less than a month. 2 down, 3 to go!!!
It is really good and teach me the basic understanding of DeepLearning back propagation and gradients optimization like Momentum, RMPS, Adam finally I learn how to use Tensorflow to train my model.
But there are some mistakes in the assignments and also in the grade so that it costs me a lot of time but useless.
by Mushfiqur R•
It was a good course on understanding various hyper-parameters, some regularization method, optimization of algorithms, various gradients and gradient checking, batch - mini batch, exponentially weighted average , some tuning algorithms and finally a small introduction to deep learning frameworks. RECOMMENDED!