Chevron Left
Вернуться к Introduction to Deep Learning

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:

326–350 из 421 отзывов о курсе Introduction to Deep Learning

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

автор: Федоров И Д

6 мая 2020 г.

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

автор: flora

20 окт. 2020 г.

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

автор: Nikhil B

27 июля 2020 г.

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

автор: Alexander K

13 дек. 2018 г.

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

автор: Saurabh K P

12 дек. 2017 г.

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

автор: Deleted A

15 янв. 2018 г.

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

автор: MP

28 июля 2019 г.

It is very good although there are some problems to run some assignments due to be too heavy computationally.

автор: Rafael J F S

21 апр. 2018 г.

Interesting content but some videos do not explain the topics well enough and some extra study is needed.

автор: Wenlong W

27 окт. 2018 г.

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

автор: Tuấn L

1 июня 2020 г.

This course is very good, but there are some topics which are very difficult to completely understand

автор: imran k

5 февр. 2020 г.

The course was awesome, I have learned lots of new things, clear some doubts, I have enjoyed a lot.

автор: giovani .

18 апр. 2020 г.

c'est terrible que la version du Keras est désactualizé, mais le cours est tellement bien!

автор: Parikshith S

2 июня 2020 г.

Amazing content.But notebooks need to be updated.

Actually requires good python knowledge

автор: Abhishek S

9 янв. 2018 г.

Some concepts should have been explained in more detail using more (or better) examples.

автор: Mark P

9 окт. 2018 г.

Yep - pretty good course that covers all the basics, and has some nice tips and tricks.

автор: Vladimir S

4 янв. 2018 г.

Хороший курс, но есть над чем поработать :)

Спасибо авторам и удачи слушателям!

автор: ELA S C

4 июля 2020 г.

This course was very Challenging and got many insights to learn.

автор: Massimo T

17 мая 2020 г.

Good teaching, the exercise preparation could be more accurate.

автор: Mauro D S

28 июля 2018 г.

Good intro to deep learning (RNN's well explained! Good job.)

автор: saraansh t

12 июля 2020 г.

A job well done. Quite responsive community and support.

автор: alessandro b

30 авг. 2021 г.

Very good, but it needs a fix on the colab homework

автор: Seongeun S

27 июля 2018 г.

Great course to get a first view of deep learning !


25 авг. 2021 г.

I am not able to do it so I quit the course

автор: sabyasachi b

24 мая 2019 г.

some lectures can be given at a slower pace