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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
1,638 classificações
377 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

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

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276 — 300 de 376 Avaliações para o Introduction to Deep 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.

por 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.

por Malay P

Mar 26, 2020

Assignments and Project provided insight into the topic but, sometimes I had to look for some topics from elsewhere as I didn't understand the course videos properly.

por Prateek K

Jun 12, 2018

The content and assignments pertaining to MLP, CNN, auto-encoders are great, but I feel it a bit lacking when it came to RNNs and LSTM with the videos/explanation.

por Wadim W

Nov 28, 2019

Intensive course with tough exercises. Very educational. Nevertheless, in my opinion, the mandatory nature of peer reviewing is no suitable for online courses.

por 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.

por 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.

por 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.

por Rmn A

Sep 08, 2020

the pronunciation need to be improved.

the course is not self contained, it must orient the participant to external more complete resources.

por Anmol G

Jun 28, 2018

The assignments are great. I wish the explanations could have been as great. Having said that, the explanation of BPTT was awesome.

por Amuj K

May 11, 2020

course content is right .one thing that i like most is programming Assignment . Real world projects seems to be fruitful for me .

por 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.

por Om S 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

por Федоров И Д

May 06, 2020

All in all, material is quite good. Programming assignments are interesting but way too easy, even the final project.

por flora

Oct 21, 2020

Could you please provide the slides/ppt ? It's necessary for reviewing again and again. Video is not as convenient.

por Nikhil B

Jul 27, 2020

Nice course. leaarned the inner workings of neural networks. Though I felt some lack in teaching actual coding part.

por Alexander K

Dec 13, 2018

Tell more about TensorFlow and Keras. It was hard to finish final project due to lack of the knowledge in that area.

por Saurabh K P

Dec 12, 2017

Lecture delivery can be improved. Content is great but may be important to break the difficult concepts even further

por Deleted A

Jan 15, 2018

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

por 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.

por 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.

por Waylon W

Oct 28, 2018

This class is great! A few professors are hard to understand but it's still OK. The homework is helpful.