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Comentários e feedback de alunos de Introduction to Deep Learning da instituição National Research University Higher School of Economics

4.6
estrelas
1,603 classificações
371 avaliações

Sobre o curso

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...

Melhores avaliações

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

TP

Aug 09, 2020

A very good course and it is truly insightful. This course deals with more on the concepts therefore I have a better understanding of what is really happening when I build deep learning models.

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226 — 250 de 370 Avaliações para o Introduction to Deep Learning

por 胡哲维

Dec 23, 2018

excellent

por franco p

Sep 29, 2019

Amazing!

por Parag H S

Aug 13, 2019

Amazing

por MAINDARGI Y R

Jul 16, 2020

Great

por Имангулов А Б

Jul 16, 2019

hard!

por heechan s

Sep 10, 2019

Good

por Sasikumar G

Jul 20, 2018

Good

por Колодин Е И

Aug 18, 2019

top

por Arsenie a

Apr 05, 2018

B

por 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.

-

por Bikhyat A

Jul 27, 2020

The course is really awesome, especially the lecturer Andrei Zimovnonv's lectures are really good. His flow, the concepts he provide, all are lucid. However, Alexander Panin's lectures are, I think quit difficult to understand. Most of the times, he suddenly delivers so fast that you can't even hear what he actually said. I think, he should work on that. And honestly, I still have lot's of confusion in the portions he covered i.e. embedding, auto-encoders, adversial networks etc. One more thing what I'd like to add is, the instructions provided in the assignment notebooks are sometime very hard to understand making me feel they're confusing and incomplete.

por 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.

por 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.

por 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.

por 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

por 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.

por 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 !

por 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!

por 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!

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.