Apr 19, 2020
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
Oct 09, 2019
I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation
by xun y•
Apr 07, 2019
Again a great course about deep learning. The course structure is very well defined, with step by step to build technical foundations in the beginning and later using open source deep learning framework to connect all the pieces together. Dr. Andrew Ng made all of them very easy to learn and sometimes I feel like I should jump out the comfortable zone he created for us.
by Willismar M C•
May 22, 2018
Very nice course about important subjects of Vanilla Neural Networks, as optimizations algorithms , regularization methods, hyper-parameters used and how to implement them in practice. A very nice chapter on the sequence of the specialization that give me understanding on important aspects of it, how to use and how to implement them. I really enjoyed each detail of it.
by Bharath S•
Jul 08, 2019
This course gives a very good idea of the overfitting problem in deep learning and different ways to overcome it. It also introduces commonly used optimization methods in deep learning. A nice introduction to tensorflow is provided in the last week's programming assignment. Overall it is a very satisfying course. Many thanks to the instructor and the entire team!
by Hari K M•
Jan 04, 2018
Key course in the specialization and covers wide array of topics which are responsible for improving the DNNs. Complicated than the first course but very well explained by Andrew Ng. Things definitely get clear after doing the programming assignments. One should definitely complete this course if one has already completed the first course. I totally recommend it.
by Bilal A•
Jan 12, 2020
Course was amazing, content was amazing, assignments was amazing.
Andrew Ng is the best teacher I have ever experienced in my life. I learned a lot from this course, these things are very difficult to learn from research papers it takes a lot of time but person with great passion of deep learning can learn all these things in just three weeks. Highly Recommended.
by Hiep P•
Nov 29, 2017
In era of deep learning bloom, know how to control network model is an important thing. And this course has them all, from tuning learning rate to speed-up convergence or applying drop-out for avoiding overfit, etc... It shows you the under-the-hood theory and brings you the knowledge to grasp the basics yourself, and actually can apply back into your projects.
by WALEED E•
Jan 08, 2019
The course is very useful for being acquainted with tuning hyper-parameters and modern optimization algorithms like momentum, RMSProp an Adam. It is also introducing how to prevent over-fitting efficiently from recent papers in addition to mini batching training data. Although it introduces TensorFlow in a brief way, the overall assessment needs some revision.
Feb 16, 2020
I strongly recommend this course since I pass an interview after finish the first and second specialization. Although it is not enough for some high-demanded company, it is a really good lecture and experience for the new beginner in neural networks. But I have to say that the project is too easy so far, I wish we will have more great exercises and projects!
by Jaime A•
Sep 08, 2017
Very clear, straight to the point, explanations with very well guided programming assignments in Python to hammer the concepts. A lot of knowledge and experience condensed in just a few hours and materials. I recommend previous exposure to Python and Machine Learning to make the most of this course (Ng's Coursera's course provides a very solid foundation)
by Amaranath B•
Oct 13, 2019
This is an amazing course , the way they had designed the transition from numpy to tensorflow was amazing. The the concepts of gradient descent with momentum to adam optimizer was great coming from your previous course , I can't express how much this has grounded my understanding. I'm pushing myself to complete the specialization. Thanks a lot everyone !
by Naveen K•
Sep 25, 2017
The course if very structured. Can't think of any improvement in course structure. Will like to thank Andrew Sir for this great effort.
As an improvement it would be great if people can be encouraged to solve problems on different dataset on internet such as kaggle. Such sources with other help can be provided as work to do after the completion of Kaggle.
by Daniel V I•
Feb 09, 2020
A fine continuing of the previous course in this specialization.
Learning optimization algorithms to improve our parameters' update, how to normalize the inputs at each and every layer, how to prioritize certain hyperparameters over others when testing.
All culminating with Tensorflow, a platform that saves us a lot of time in programming Neural Networks.
by Gaurab B•
Jun 19, 2019
Brilliant material altogether.. almost a compulsory course for researchers diving on the ocean of deep learning.. While I was reading papers on deep learning I came across all these terms but couldn't understand it.. Now the picture is pretty clear... Thanks Prof. Andrew Ng for this wonderful effort. I have already recommended this course to everyone.
by zhijun l•
Dec 06, 2018
A great course talks about the detail in building Neural networks. With the first course as a foundation, student taking this definitely will get a better understanding on hyperparameter tuning and optimization, in addition on training neural networks. I recommend this course to those who would like to know neural networks more than just the concept!!
by Oliver M•
Aug 14, 2017
Having completed Udacity 730 on Tensorflow, I found Andrew Ng filled crucial gaps in my understanding. He is not afraid of presenting some maths to build intuition, but he always presents it in a straightforward way. Compare his explanation of Adam optimisation with the source paper on the subject. Andrew boils it down and serves it up beautifully.
by Adail M R•
Sep 13, 2017
Once more, Prof. Ng show in his simple style how to tackle the tough subject of hyperparameter tuning, pointing to several techniques and helping us selecting the most appropriate ones for the task at hand. The Tensorflow introduction is also very effective and engaging! Looking forward to advance my knowledge and experience with the next courses!
by Diego A P B•
Mar 06, 2018
Hyperparameter tuning and the other techniques seen in this course are not perceived to be the most fashionable areas of machine learning and deep learning. Nonetheless, they are crucial parts, and thus the techniques shown in this course will show you how to save great amounts of time and headache when trying to improve and finetune your models.
by Nestor H•
Jun 06, 2018
It was a great course to take. I could grab basic knowledge on TensorFlow and on some optimization techniques. I consider all the optimization algorithms are based on gradient descent, it is just that they tweak some parameters, but they are gradient-descent like algorithms. In summary, Dr. Ng is a genius and it is worth taking all his classes.
by Jay P G•
Dec 31, 2019
After knowing the basics of Deep Learning and Neural Networks (From the course 1) , this course explains the crux of improving and tuning of the neural networks and it's parameters and Hyper parameters . And the intro to tensor flow at last was just awesome(not exaggerating it!!!) . Congrats to Andrew and his team for such an awesome course .
by Shivdas P•
Dec 24, 2019
This course extends what has been taught in the preceding course, especially the different hyper parameters and optimisation strategies. Getting started with TensorFlow in a complete end-to-end example has been one of the things I was looking for and this course puts all that and many other things into perspective. Thanks Andrew and team !!
by Tamas K•
Aug 03, 2019
The course was great, thank you! However, I'm really looking forward using Tensorflow in C++ or Swift. The obscure, untyped nature of Python facilitates cargo-cult habits, creates some mystic fog around the variables (since it's not explicit if e.g. 'cost' is a concrete float or an entire computation waiting to be executed) and error-prone.
by Eulier A G M•
Aug 31, 2019
The course is very well structured, most of the topics here is perhaps kind of boring due the lack of real-problems projects, but if you stick to it and learn the concepts, will boost your understanding when using Deep Neural Network Frameworks, such as Tensorflow. That makes creating DNN easy to set, understand and apply to your problems.
by Suhas P•
Sep 21, 2017
Introduction to TensorFlow was wonderful. This course has helped me visualize and experience end to end flow of an actual machine learning project that helped a lot. Thanks to Andrew for taking efforts to design the course in a user friendly way. Programming tips are intuitive, helps save your time and allows you to focus more on learning.
by Chandan N•
Nov 27, 2019
Great insights into the theory of regularization and famous optimization algorithms like RMSProp and Adam. Helps in developing intuition regarding these algorithms work and implementing them from scratch was pretty rewarding as well.
As usual, Prof Andrew Ng patiently explains the theory and helps in building understanding of the material.
by Saransh M•
Aug 20, 2019
Started from the basics but made sure that they provided an in depth understanding of some very important concepts like hyperparameters and regularization will well structured quizzes and interesting programming assignments. Really liked the course and would suggest it to anyone trying to set their feet in the field of ML or Deep Learning