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국립 연구 고등 경제 대학의 Introduction to Deep Learning 학습자 리뷰 및 피드백

4.6
별점
1,497개의 평가
349개의 리뷰

강좌 소개

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...

최상위 리뷰

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

AM

May 29, 2020

The hardest, yet most satisfying course I've ever taken in deep learning, by the end of the course I was doing stuff that was borderline sci-fi and that was just "introduction" to deep learning

필터링 기준:

Introduction to Deep Learning의 349개 리뷰 중 226~250

교육 기관: Aparna S

Jan 06, 2020

The material that it is trying to cover is very good. The programming assignments are intuitive with fill in the blanks kind of approach. Finishing them and the quizzes was a breeze.

But if you are new to tensorflow and Keras and a picky like me in wanting to know exactly what is going on and how, this course is wanting details.

It does have few other minor hitches -

-It has missing links to resources (you can dig them out though)

-mistakes in slides (that they embarrassingly correct inside)

-If you care about math, it might be disappointing when you see formulae with ill-defined variables and assumptions about notations that are not discussed. If you have a background, and do simple web search you will find it out in no time though.

-

교육 기관: Arend Z

Feb 09, 2018

Very helpful to get a good basic understanding of the different types of neural networks and their application. After finishing the course, I do not yet feel confident enough to build my own neural network applications. Maybe this can be solved by having more programming assignments at 'beginner' level, before 'stepping up' the complexity.

The provided 'example' codes - that work after successful completion - serve as a good starting point to build your own neural networks.

교육 기관: Anselmo F

Mar 22, 2020

Very interesting course, the notebooks are very useful and all the concepts are very well motivated and explained. I just found some bugs in the course and had some problems with the explanations of week 4 and I believe week 5 lacked the explanation of some basic concepts, but all of these gaps could be filled with a research of additional material. Anyway, I recommend this even for beginners, all you need to know are derivatives and some Python basics.

교육 기관: Abhinav S

Apr 23, 2018

It is not an easy course, but the course projects are very nice. I really liked the RNN and CNN parts of this course very well explained and had some rigour to it.

My only complaint about the course is that it is not self contained. You will have to read up a lot more and refer to other sources on the internet to get a firm grasp of what is being taught and then go ahead to tackle the exercises.

교육 기관: 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

교육 기관: 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.

교육 기관: Saptashwa B

Jan 21, 2020

Very nice course with a great project in the end. I just think this course is little too big (7 weeks) and still at times fail to cover important points in detail. I assume they are covered in the next courses of the specialization. Specially convolutional neural network for image classification requires better explanations at some part. Just my opinion though !

교육 기관: Juho H

Jun 25, 2020

Very challenging assignments, and unfortunately using the old version of Tensorflow. On the other hand, you really get an understanding on many things other courses skip (like the different optimizer algorithms), and the labs are very interesting. But you really need to have already fairly much experience in machine learning before tackling this one!

교육 기관: Ipsita S

Feb 17, 2020

As I'm familiar with deep learning I took a advanced course in order to learn new things and enhance what I already know. I have given a four star because I didn't find things new for me but I continued because the course is well structured and the assignments actually were helpful for practical learning.

Overall a good experience for me!

교육 기관: Emanuel P F

Jan 09, 2019

It is not a introductory course! The course provides an excellent path showing the most tools in deep learning techniques but you have to spend more time looking for additional material to supplementary this course. In general you will learn the basic about Neural Networks, Convolutional Neural Networks, and Natural Language Processing.

교육 기관: Alexey Z

Mar 19, 2020

Autoencoders, RNN: Theory ovekill, which seems to be pretty useless, as after listening and trying to follow the lectures logic, you need to go outside to read explanations. E.g., after lectures I had 0 understanding of how LSTM is implemented, how it really works, even how actually it helps avoding gradient expls/vanishing.

교육 기관: Γεώργιος Κ

Jan 13, 2020

This was absolutely an interesting and enlightening course. There are things left unexplained and appear from nowhere in the programming assignment like RMSprop. Though the assignments can be passed even with these dark spots I think this is a reason that this is not a five-star course. In fact, I would rate it as 4.5 stars.

교육 기관: 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.

교육 기관: GOUTAM K

May 28, 2020

Lectures were short and to understand the topic, we need to browse those topics online. Programming assignments were tough and interesting but mostly pre-coded. But still the code quality was good and reading the code was interesting. Overall a good course but not much recommendable for a beginner.

교육 기관: Yaran J

Jan 06, 2019

Good overview of deep learning topics like CNN and RNN, and also hands on coding assignment of Tensorflow. However, this is a big gap between the video material and the programming assignment. Need to add more training for Tensorflow before deep learning models. And the instructors speak too fast.

교육 기관: Max P Z

Nov 19, 2017

The content of the course and programming assignments is well designed. However, there're some technical issues with the assignments (eg. unable to submit the results for honor content). And some requirements for the accuracy/loss in the programming assignments are really too high.

교육 기관: 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.

교육 기관: Tue R L C

Mar 20, 2018

This is a relative new courses which shows in some of the assignments e.g. minor mistakes and weird hacks required to pass them. The final project is a bit of a let down as it basically requires the user to do some data processing in python but no "real" machine learning.

교육 기관: Gonzalo C

Jun 20, 2020

You should record again all the videos of week 4, because the pronunciation in that videos are not good enough to understand well all the details, and It's kind annoying to listen all the videos, and keep listening for long time. The rest was a great course

교육 기관: 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.

교육 기관: Abhinav U

Dec 02, 2017

It's a good course for people with some prior experience and background in machine learning (specially neural networks). The exercises and projects were a bit difficult and needed effort to get correct but helped reinforce the concepts.

교육 기관: Milos V

Jan 08, 2019

Interesting and useful course. Capstone project was quite difficult, but I learned a lot - so I do not want to complain about it. Maybe a bit more code-related things during the lectures would be useful to make capstone project easier.

교육 기관: nicole s

Mar 18, 2018

Very good content and teachers. Indeed advanced level, for the less advanced it would have been helpful to include some more clarifications towards solving the assignments and the mathematical derivation of the main concepts.

교육 기관: Georgios P (

Apr 26, 2020

It is a good course overall, but some subjects feel a bit rushes. Also, it would be much better if authors were adding a week for learning the tools that are used in program assignments (Tensorflow and Keras specifically).

교육 기관: Sachin

Mar 02, 2019

really nice course to hone your skills. but sometimes the assignments are really really tough and no hint is provided how to solve them. i was having problem because of my weak python skills. afterall course is relly nice