Jan 14, 2020
After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.
Dec 24, 2017
Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.
創建者 Rajeev G•
May 09, 2020
Took the course to retest my knowledge in Deep learning. Have completed this course some time back. Without certificate. Professor has covered each of these topics in good detail. Practice workbooks and assignments are really helpful and provide a great start for deep learning enthusiasts.
創建者 Xiang J•
Oct 25, 2019
Really like the assignments in this course, which gives me hands-on experience with advanced knowledge such as Adam optimizer, gradient checking. Tensorflow v1 assignment is also good, but I am not sure whether API is still relevant as Keras based API for tensorflow v2 is already released.
創建者 Tarush S•
May 16, 2019
With this course, even the beginner can understand why what happens when tuning and optimizing a neural network model. With easy to understand methodology and great explanation, I highly recommend this course for anyone who wants to go deeper into deep learning and understand the workings.
創建者 Meghdad P•
Aug 06, 2018
Very helpful learning material.
I'm still a bit confused though, even after passing the exams and exercises, but I think its mostly because I've lost grasp on mathematics. So, the blame is on me not coursera.
Hopefully I would fit more in the Deep Learning world by finishing up the course ;)
創建者 Millard A C•
Feb 10, 2018
This is a great course and you get to do real programming and training of a Deep Neural network. Andrew Ng is an excellent instructor. The final assignment wasn't hard but the syntax was difficult to follow. Using the forum and the Tensorflow documentation you can make your way through.
創建者 Bill T•
Feb 04, 2018
This builds on the basics from the first course with some important techniques (such as Xavier initialization, Adam optimization, and batchnorm) and ends with an introduction to implementing these in TensorFlow. Fast-moving but well taught with a good mix of theory and hands-on exercises.
創建者 Yevhen D•
Jun 24, 2020
Awesome course. Theory and practise in the right proportion. Programming assignments are useful, interesting and use modern technologies like Python or TensorFlow. Question quizzes are not too hard but help to repeated theory. Also, I liked interviews with great people from Deep Learning.
創建者 Sari S•
Jul 25, 2019
I am totally enlightened by this course. A lot of the concepts covered were completely new to me and very helpful in building a good performing neural network. The lectures were in depth and very well organized. The contents are not something you will come across in other tutorial sites.
創建者 Bryan W•
Jan 18, 2018
A great refresher to Andrew's original ML course at first, but also later is learning current deep learning current mindset at work. Great pace, great course, and great programming assignments. Makes me want to see the 3rd course for (i hope) more challenging programming assignments :) .
創建者 harm l•
Sep 03, 2017
Gave me a clear understanding on how to improve the calculus on a neural network. Computational software has advanced from programming in R of Python to software frameworks, hiding a lot of the math. Needs another study of the software frameworks though!
Thanks for the opportunity to join.
創建者 Maryam H•
Jun 19, 2019
prof. Ng's teaching was so great. some tricky details taught that I never considered them before. when I read the textbook, it was easy to understand and repetitive. I've learned simple and clean implementation. in overall it was important, simple, understandable, time efficient course.
創建者 Rahul K•
Feb 28, 2018
A very well structured course on some of the most overlooked (but critical) elements in Deep Learning. Prof. Andrew Ng definitely makes everything seem easy; he breaks down even the most complex of optimization algorithms and explains it with sheer simplicity. Would definitely recommend!
創建者 Pranaya M•
Aug 06, 2018
Course has been designed so well that even a aspiring beginner can learn the concepts very well.
Every student who wants to begin their career in the field of Deep Learning must follow this course.
Especially the tensor flow concept is taught very well with the help of exercise tutorial.
創建者 David J•
Jan 07, 2018
Thank you Andrew and Team for this course. I must say the course has surprised me and I have myself surprised my level of learning. But all credit to the way course is laid out and the step by step method of progress along with strong conceptual explanation helps a lot. Thank you again
創建者 Rahul V•
Jun 01, 2020
Awesome Course! :)
Andrew is really the best instructor... He makes problems very easy to solve.
The content is fantastic...
The best part of this course is Optimization algorithms.
I loved every video and content with best explanation on hyperparameter tuning...
Adam optimization is best
創建者 Lav M•
Apr 15, 2020
A great course, with deep understanding of all important hyperparameters and the related concepts important to tune the deep neural networks. Lectures are up to the mark and so are the programming assignments. Thanks a lot Andrew Ng and Coursera for making it possible for me to learn.
創建者 Alejandro R V•
Jan 02, 2018
As usual, another incredible course taught by a really good teacher. I strongly recommend it to anyone who wants to get a firm garsp about optimization algorithms and how they really work, apart from hyperparameter tunning and regularization methods for bias/variance. Thank Andrew Ng!
創建者 Sanjay R B•
Jun 16, 2019
Very helpful in building on the foundation in neural networks and deep learning with practical experience. The programming assignments are reinforce key concepts and are a great asset to keep after the class and apply in projects. Andrew is doing great work bringing AI to the masses!
May 04, 2019
Nice illustration of the tricks including Batch-Norm, Optimization as well as Dropout, etc. Sometimes the lack of the theory is sort of unstatisfying, but considering the difficulty of a comprehensive intro for all of the above, it has been good enough for beginners to catch up with.
創建者 A S M A M•
Jan 01, 2018
While the first course in the specialization is the perfect introduction to the realm of NN, this course is the place where I learned to implement a true Deep Network. It talks about various optimizations and parameters of the DL models. Bonus, it introduces the tensorflow framework.
創建者 Ananth K•
Oct 24, 2017
Great course! Very well laid out approach to tuning a deep neural network. FInal introduction to Tensorflow was useful, but I think a lot of information was compressed into a single video. Suggest spreading this a little more. The Tensorflow programming assignment was pretty good.
創建者 Alberto B•
Oct 07, 2017
Genial curso en el que aprender como optimizar tu red modificando una serie de parámetros y usando diferentes algoritmos. Ademas genial introducción a Tensorflow con el que avanzar en el montaje de redes de manera rápida. Recomendado totalmente tras realizar el curso anterior a este.
創建者 Anurag A•
Sep 10, 2017
This course is awesome. I never had this deep understanding of tuning hyperparameters, batch normalization and regularization before taking this course, though I went through several online material. The Tensorflow introduction and subsequent programming assignment is also excellent.
創建者 Prabhat K P•
Jan 10, 2020
The best course ever. I am highly impressed with the way Andrew Sir teaches and the depth of the topic, that he explains. You will never be left with a question unanswered. I am grateful to you sir, it made my life. Looking forward to complete the rest of the specialization courses.
創建者 Taras M•
Jul 26, 2018
It would be super cool if this course could be extended with pytorch just to compare with tensorflow. Usually courses are extended on udemy, for instance (not a marketing, just a comparison), even after all the materials are completed. It would be sand to have this course abandoned.