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Отзывы учащихся о курсе Introduction to Deep Learning от партнера НИУ ВШЭ

Оценки: 1,806
Рецензии: 421

О курсе

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:

Лучшие рецензии

19 сент. 2019 г.

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

8 авг. 2020 г.

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.

Фильтр по:

301–325 из 420 отзывов о курсе Introduction to Deep Learning

автор: Evangelos-Iason M

23 июня 2020 г.

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.

автор: Daniel R G

19 сент. 2021 г.

Excellent course, with great and interesting material, the only detail was one of the instructors whom I could not understand much because of the pronunciation he had and that he spoke very fast

автор: Murad O

17 дек. 2017 г.

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.

автор: Пронина Д А

22 янв. 2020 г.

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.

автор: Evgeny K

23 июня 2018 г.

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.

автор: Georgiy I

7 мая 2018 г.

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.

автор: LIVESH K

26 авг. 2021 г.

good syllabus and content but instructors just read from the slides and put little effort into actually explaining what is written. Not recommended for complete beginners.

автор: Udaya B S

23 апр. 2020 г.

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.

автор: Vishal A

7 июля 2020 г.

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.

автор: Orazaev A

1 февр. 2018 г.

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.

автор: kareem j

5 февр. 2020 г.

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.

автор: Jesper H L

24 июля 2019 г.

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.

автор: Malay P

26 мар. 2020 г.

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.

автор: Prateek K

12 июня 2018 г.

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.

автор: Wadim W

28 нояб. 2019 г.

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

автор: Andrea C

30 мар. 2019 г.

Very good content and top notch exercises. But sometimes the lectures are not fully comprehensible without a lot of additional reading from other sources.

автор: Zewei W

1 февр. 2018 г.

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.

автор: Jun K

1 мая 2019 г.

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.

автор: Смирнов К С

13 янв. 2021 г.

The course is very good but one of the speaker - Alexander Panin - has very bad english pronunciation. It was too difficult to understand what he told

автор: Rmn A

8 сент. 2020 г.

the pronunciation need to be improved.

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

автор: Anmol g

28 июня 2018 г.

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

автор: Amuj K

11 мая 2020 г.

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

автор: Clément S

19 дек. 2020 г.

Notebooks are lacking explanations and lecturers do not have a good Ensglish accent. Otherwise, great and challenging content

автор: Pablo V I

17 июня 2018 г.

This course is not a deep learning introduction. The assignments are challenged and well organized, specially, the last one.

автор: Om S P

25 июня 2019 г.

The peer review is slightly problematic since there is no check on whether the grader is doing the grading properly or not