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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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251 — 275 de 370 Avaliações para o Introduction to Deep Learning

por 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.

por 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.

por 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.

por 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

por 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.

por Thomas L

Aug 29, 2020

The course is greatly taught and benefits from having several teachers, each having their own touch and approach to the material.

An upgrade of the programming assignments to the latest version of tensorflow would however be more than welcome!

por 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.

por 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.

por 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.

por 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).

por 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

por Adam S

Feb 26, 2018

The course is very good. The last assignment was pretty ambitions with the image captioning but i am glad they did it. Some of the lectures the english is very difficult to follow. Other than that really helpful course.

por 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.

por Hamlet B

Jan 20, 2018

This course is incredibly challenging and the assignments can be frustrating with little guidance, and high bar to pass graders. I give it a high rating because it really pushed me to learn and master details

por Meetkumar R

May 02, 2020

It was a good experience as it introduced some basic concepts of Deep-Learning. But knowledge delivery was not good as it was hard to understand what the instructor was saying due to some language issues.

por Sergio A M V

Sep 02, 2020

This must be updated to tensorflow 2 :) there is a professor that is really hard to understand what he is saying sometimes, also In the subtitles show inaudible. Maybe fix the subtitles is good enough

por Evangelos-Iason M

Jun 23, 2020

The overall course quality is very decent with real industry applications. I think if you added some additional lecture videos, the course would be better; sometimes it feels like we are in a rush.

por Murad O

Dec 17, 2017

I found the content to be interesting and on a good level of advancement, but I also found the exercises to be buggy sometimes or not well thought, which cost a lot of extra time spent on it.

por Пронина Д А

Jan 22, 2020

The course was quite useful, but I didn’t really like how the practical tasks were compiled. For some tasks, a lot of time was spent only because of an incorrect description of the task.

por 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.

por Georgiy I

May 07, 2018

Great course for recap of crucial things in DL. But, materials seems useless for people, who don't already have an appropriate knowledge about this field of machine learning.

por Udaya B S

Apr 23, 2020

I found the course a bit difficult, but probably apt for advanced learners. Occasionally the lack of clear instructions at places (esp in the final week) hurt my progress.

por Vishal A

Jul 07, 2020

I suggest this course to all who want learn about deep learning and computer vision .

this course is helpful to gain knowledge that how to apply cnn and rnn in our model.

por Orazaev A

Feb 02, 2018

Good introductoral material. Most of assignments are done well, but some of them still a bit raw and to solve them students often change code written by course creators.

por kareem j

Feb 05, 2020

The content is great, but sometimes some concepts need more illustration. Also, sometimes the language is not spoken perfectly which makes it a bit hard to understand.