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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
1,660 classificações
384 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
19 de Set de 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
8 de Ago de 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 384 Avaliações para o Introduction to Deep Learning

por Akshit V

13 de Jul de 2019

Great Course!

por edward j

28 de Fev de 2018

Great course!

por Ajayi E A

4 de Jul de 2020

Satisfactory

por Alfonso M

31 de Jan de 2019

Good course.

por Krishna H

10 de Jun de 2020

Exemplary!

por Alex

1 de Mar de 2018

Nice work.

por Xiao M

18 de Dez de 2017

Very gooda

por Sbabti M z

27 de Out de 2020

exxellent

por Kollipaka s

22 de Mai de 2020

very good

por M A B

25 de Fev de 2019

Excellent

por 胡哲维

23 de Dez de 2018

excellent

por franco p

29 de Set de 2019

Amazing!

por Parag H S

13 de Ago de 2019

Amazing

por MAINDARGI Y R

16 de Jul de 2020

Great

por Имангулов А Б

16 de Jul de 2019

hard!

por heechan s

10 de Set de 2019

Good

por Sasikumar G

19 de Jul de 2018

Good

por Колодин Е И

18 de Ago de 2019

top

por Arsenie a

5 de Abr de 2018

B

por Aparna S

6 de Jan de 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

26 de Jul de 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

9 de Fev de 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

22 de Mar de 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

22 de Abr de 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

26 de Jun de 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