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Learner Reviews & Feedback for Introduction to Deep Learning by National Research University Higher School of Economics

4.6
1,123 ratings
254 reviews

About the Course

The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. Learners will study all popular building blocks of neural networks including fully connected layers, convolutional and recurrent layers. Learners will use these building blocks to define complex modern architectures in TensorFlow and Keras frameworks. In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image. The prerequisites for this course are: 1) Basic knowledge of Python. 2) Basic linear algebra and probability. Please note that this is an advanced course and we assume basic knowledge of machine learning. You should understand: 1) Linear regression: mean squared error, analytical solution. 2) Logistic regression: model, cross-entropy loss, class probability estimation. 3) Gradient descent for linear models. Derivatives of MSE and cross-entropy loss functions. 4) The problem of overfitting. 5) Regularization for linear models. Do you have technical problems? Write to us: coursera@hse.ru...

Top reviews

DK

Sep 20, 2019

one of the excellent courses in deep learning. As stated its advanced and enjoyed a lot in solving the assignments. looking forward for more such courses especially in Natural language processing

AK

Jun 02, 2019

one of the best courses I have attended. clear explanation, clear examples, amazing quizzes & Programming Assignment this course is advanced level, don't enroll it if you are a new starter.

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201 - 225 of 254 Reviews for Introduction to Deep Learning

By Jay U

Jun 26, 2018

+ Instructors go into considerable theoretical depth and are very knowledgeable. + Great assignments, but can be pretty challenging+ You will learning a lot by taking this course.-Some instructors are much better than others- Instructors rely too much on slide reading. Lectures lack interactivity other than an occasional pop question.- Discussion groups are not active. Many posts go unanswered

By Rainer-Anton E

Jan 15, 2018

I really love the machine learning courses from National Research University Higher School of Economics. Thank you!

By Eric V

May 26, 2018

Great course with challenging assignments.

By Zewei W

Feb 01, 2018

it is a good course with challengeable PAs and nice teachers, i like it.

Anyway... if there is more ASSERT statements in PAs, students may be much happy.

By Zhen Y

Jan 31, 2018

I found the first assignment (Week2) very difficult if you didn't have enough experience in Tensorflow to start with. Later on, the assignments became more enjoyable.

The course is more advanced than Machine Learning and DeepLearning.AI. Lots of concepts are gone through very quickly. It is not ideal if you are new to the subject. However, it covers great details in a short course.

By Abhishek S

Jan 10, 2018

Some concepts should have been explained in more detail using more (or better) examples.

By Rafael J F S

Apr 21, 2018

Interesting content but some videos do not explain the topics well enough and some extra study is needed.

By Evgeny K

Jun 23, 2018

I didn't like some lectors. However, the course itself was a great start to learn Deep Learning for me. It covered fundamental topics very clearly, so I appreciated this very much.

By Pablo V I

Jun 17, 2018

This course is not a deep learning introduction. The assignments are challenged and well organized, specially, the last one.

By Andrei V

Jun 08, 2018

Nice intro to DL. Final assignement is quite hard to accomplish, as you don't know the goal - loss should not too small, not too big (but are the boundaries?). For me it was ok, as I'm running on GPUs, but it should be painfull path for CPU folks.

By Ting Y

Apr 13, 2018

Comprehensive intro of deep learning

By Jun K

May 02, 2019

Some programming assignments were not instructed enough, so it's very hard to solve them without discussion forums. But this is good course as a whole.

By Driaan J

Apr 29, 2019

The content of the course is really excellent, and the lecturers' knowledge is just superb.

The only drawback of the course is that the lecturers' native language is not English, and accordingly it is sometimes difficult to understand them. But there are subtext to the lectures in English that one can refer to.

By Andrea C

Mar 30, 2019

Very good content and top notch exercises. But sometimes the lectures are not fully comprehensible without a lot of additional reading from other sources.

By SABYASACHI B

May 25, 2019

some lectures can be given at a slower pace

By J.Om P

Jun 25, 2019

The peer review is slightly problematic since there is no check on whether the grader is doing the grading properly or not

By Jesper H L

Jul 24, 2019

A good course. But do not think that you can do this course og you are new to AI. IT tales you to the latest, but you midt know the finest and python before you start.

By Pablo M P

Jul 28, 2019

It is very good although there are some problems to run some assignments due to be too heavy computationally.

By Margarita C

Jul 29, 2019

My impression of the course is controversial, like it itself is: an introduction to advanced DL. Tough and frustrating for the first experience in DL. The course was useful, but, as everyone notes, in the end you learn from materials you find in the Internet to complete the tasks.

By Tiandong W

Sep 12, 2019

This is an ADVANCED DL course. If you have already learned Andrew Ng's deeplearning.ai course or other basic course, this course is good for you as a test. But if you don't know DL at all, this is not for you.

By Ramin A

Jan 21, 2019

Overall I enjoyed the course, but it lacks structure. Some materials are assumed to be well known by the learner and surprisingly some easier ones are not. I like to see the math, but it needs more materials to support it. Most instructor's have very heavy accent and tend to speak too quickly, I find myself rewinding multiple times just to figure out what was being said. Homework's are not too difficult, and are enjoyable. Except for the last one where you need to wait for a peer review. I think this can be a flagship course with more efforts.

By 唐志强

Jul 30, 2018

各种口音的英文发音对母语为非英语的学生很困难

By Zhaoqing X

Jul 20, 2018

Well, I think it's a good course for introducing us to Deep Learning and it has better(tougher) assignments than Andrew's. It also covers more knowledge than Andrew's. But the quality of the course is not that good. The Russian accent is not important because my native language is not English as well, but the assignments are frustrating. The mentors cannot answer the questions that widely appears in the course.

By Carlos V

Oct 07, 2018

The Course is good, probably should be called introduction to advance deep learning, the complexity of the assignments make you put lots of efforts around them, that is rewarding at the end, make sure you have plenty of time to dedicate to this Course, one thing the Course could improve on is to try to minimize the switch between libraries and the low-level coding with high-level coding between TF and Keras sometimes it creates confusion.

By Juan C E

Feb 27, 2018

The quality of some of the video session is not good, especially for RNN's. Very general, badly explained and little practical information for the practical assignments. Yor have to "learn" the material, not just look for additional information, from other sources.

The pratical assignments are note always well designed, and some are full of flaws. After many many hours of dealing with some of them, you get the impression that you've passed the assignment but not learned much.