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Learner Reviews & Feedback for Neural Networks and Deep Learning by deeplearning.ai

4.9
60,425 ratings
11,451 reviews

About the Course

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago. In this course, you will learn the foundations of deep learning. When you finish this class, you will: - Understand the major technology trends driving Deep Learning - Be able to build, train and apply fully connected deep neural networks - Know how to implement efficient (vectorized) neural networks - Understand the key parameters in a neural network's architecture This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions. This is the first course of the Deep Learning Specialization....

Top reviews

BC

Dec 04, 2018

Extremely helpful review of the basics, rooted in mathematics, but not overly cumbersome. Very clear, and example coding exercises greatly improved my understanding of the importance of vectorization.

SG

Jul 15, 2019

Dear Andrew! Thank you so very much for making me belive in myself as a machine learning engineer. Your lectures & excercises are like "shoulders of Giants" on which a good student can stand out high.

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10876 - 10900 of 11,237 Reviews for Neural Networks and Deep Learning

By Gaetan J d B

Apr 28, 2019

Would be great to get the slides in pdf (as on the ML course)

By Hany T

Apr 01, 2019

It is great the we build every thing from scratch. However, the audio quality would have been better.

By Grant C

May 11, 2019

Not as good as the Machine Learning course, but still interesting!

By Daniel C A

May 10, 2019

The course is great... Some concepts should be more clear in the firsts slides as "What is Artificial Inteligente, what areas it may apply, what is Machine learning, what divisions does it have, ... ". The explanation is more really calculus than AI, but it's the core of the technology... It's a great course.

By Jaime G

Apr 05, 2019

Some typos

By Xumin C

Apr 06, 2019

good beginning for learning foundation of deep learning

By Youssef K E

Mar 24, 2019

I think it would be better if there was more sophisticated applications, the 'image classification' application in the last week was a little bit direct with no to little hard-earned experience.

By Philip P R

Mar 24, 2019

Great course!! Having done Andrew Ng's course 'Machine Learning' before this one, I learned some things for the second time. The programming assignments are very meticulously prepared by the course's designers, to the point that I felt a bit too MUCH was already done for me. I still learned a ton, though.

By 成文辉

Mar 23, 2019

The assignments are so important that you have to finish them by yourselves.

By João M C d N

Mar 23, 2019

I wish it would've delved deeper into the backpropagation part. Coming from the Machine Learning course, I found this one much simpler and sometimes repetitive, but it's probably a good introduction to next courses in this specialisation. Overall, I liked it and I think it was useful.

By Elco B

Mar 23, 2019

good intro to the main concepts.

By Rajib C

Mar 25, 2019

A brilliant course designed. Helpful to start as a beginner, just that practical application other than through JUPYTER should be incorporated otherwise the course is perfect.

By VIGNESH V

Apr 07, 2019

good to learn

By JAGANPRASATH V

Apr 08, 2019

yeah i learned many new things one of the best

By Alejandra S T

Apr 08, 2019

i wish there were examples in the videos

By 林海涛

Apr 08, 2019

could add some courses on the detail about analysis on derivatives of different structures of neural network .

By aasritha m

Apr 09, 2019

good

By Prafful P

Mar 28, 2019

This course provides an in-depth view of how neural networks work and how each parameter is calculated (including derivations for the curious Joe). I wish it had more practical approach as the programming assignments were based entirely on what was taught in course. They should have also included some application based learning.

By Manuel F

Mar 27, 2019

Great course for taking first steps in machine learning. I was surprised to see that it doesn't take huge and complex algorithms to build a learning neural network, but only a handful of mathematical functions molded into code. The underlying math is explained well, but only to a certain point. It is sufficient to complete the course, though. I definitely recommend this course, which has left me wanting more...

The only nuisance I found is that the video captions contain many errors, which makes things unnecessarily hard, especially for non-native speakers.

By Vasily

Apr 10, 2019

I've enrolled on the Deep Learning specialization right after completing Professor Ng Machine learning course. because i was exited to get more in-depth understanding of the subject.

My expectation from it were that it's more about multi-layer NN rather than NN in general.

As a result 3 out of 4 weeks of the material here felt mostly repetitive for me just with slightly different notation and python instead of octave.

I would still recommend it as your first NN course or if you're planning to enrol on full specialization just keep in mind that 3/4 of it's contents is introductory material about NN and manage your time accordingly.

By Matthew G

Apr 11, 2019

At first it was hard to get into Python having spent 12 weeks in the Stanford class which utilizes Matlab throughout. I find the Jupyter notebooks to be harder to debug and often I would lose my work if I didn't have the notebook every few minutes religiously. However, it seems that Python is preferred to Matlab in the machine learning community so I am glad that the course was taught in Python. I also felt that the lectures were very superficial and lacking compared to the lectures by the same instructor in the Stanford course. However, having completed that course initially I already understood most of the stuff that was glossed over in this course. The lectures also seemed a bit disorganized and it was hard to go back through and find information in the lectures. I also wish that they kept the tradition of weekly slide summaries as they did in the previous class to make it easy to go back and find information. The Stanford course was definitely a 5 star course, this one falls a bit short though.

By Dmitry M

Mar 29, 2019

Too basic.

By Valentino C

Apr 11, 2019

I would like the mathematics to be tested on more heavily. Overall I enjoyed this course and learned about outlining the structure of neural networks, writing clean code, and vectorizing with python.

By Timo T

Apr 12, 2019

Nice refresher for the basic stuff

By Anthony B

Mar 30, 2019

I loved the course but I feel like what I learned is a bit shallow. The programming exercises all but gave the right answer so it was mostly a matter of copy pasting a formula from a section or two above the code. I understand why that's necessary as I don't think as many students will stick through the course if the answers aren't easily accessible but I feel as though without the process of searching and contemplating on my solutions the knowledge will not remain in my brain long. Having said that, I cannot stress enough how well done the exercises and course was. I will certainly be continuing this series. That one point is just my reason for 4 stars instead of 5. I may be being too picky. Thank you! :)