Chevron Left
Volver a Introduction to Deep Learning

Opiniones y comentarios de aprendices correspondientes a Introduction to Deep Learning por parte de HSE University

4.5
estrellas
1,843 calificaciones
431 reseña

Acerca del Curso

The goal of this online 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....

Principales reseñas

DK
19 de sep. 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

AM
28 de may. de 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

Filtrar por:

351 - 375 de 429 revisiones para Introduction to Deep Learning

por Massimo T

17 de may. de 2020

Good teaching, the exercise preparation could be more accurate.

por Mauro D S

28 de jul. de 2018

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

por saraansh t

12 de jul. de 2020

A job well done. Quite responsive community and support.

por alessandro b

30 de ago. de 2021

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

por Seongeun S

27 de jul. de 2018

Great course to get a first view of deep learning !

por SIDHARTH K

25 de ago. de 2021

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

por sabyasachi b

24 de may. de 2019

some lectures can be given at a slower pace

por Eric V

26 de may. de 2018

Great course with challenging assignments.

por Hrisikesh B

10 de ene. de 2022

Videos provided can be more detailed.

por Ting Y

13 de abr. de 2018

Comprehensive intro of deep learning

por Siddharth P

25 de ene. de 2020

Tensorflow 2 would have been great

por hhwaiting

23 de ago. de 2018

课程有一定难度,需要有比较好的先验知识,但课程作业设置非常锻炼人

por Olayinka E O

9 de dic. de 2020

Lots of Interesting exercises.

por Tadas Š

15 de oct. de 2019

Quite good - not too basic.

por Abhishek S

18 de may. de 2020

Challenging and helpful !

por Chinemelu E

12 de ene. de 2019

I love the material!!

por Heider D L

3 de ago. de 2020

Really hard lol

por Vinícius L

15 de jul. de 2020

Very good.

por Robert K

21 de may. de 2018

I've dived into this course only AFTER completing Andrew Ng's specialization "deep learning". In that sense this was a nice "revision" with additional set of exercises. Some of the topics introduced were nice exercise in ultimately "testing" your knowledge from other sources. Having said this, you really need previous exposure to machine learning, and I'd also say - deep learning.

But it doesn't give much beyond this point. Lecturers vary in terms of knowledge, or rather the ability to clearly present it. Coursera serves might not be enough for most exercises, and it pushes you to set-up your own machine (if you have a proper one) or configure one on the cloud. With many services it is rather easy now.

Overall, I recommend it as a review, an introduction AFTER some exposure. Some additional material might be new to you, but no necessarily if you followed other courses. I am more eager to look into further courses in the specialization.

por Angela W

7 de jul. de 2020

The topics are great, but many of the speakers have heavy accents and the written transcript is often nonsensical. All in all, I did not enjoy watching the lecture videos and found the course pretty tedious. What is very cool is that the programming assignments can be done on google colab (with instructions) where you can use GPUs for free.

In summary, I feel that I did learn a lot and the idea of the course is great, but faced with the prospect of having to watch more of these videos to complete the specialization, I cancelled my subscription after finishing this course instead.

por Ramin A

21 de ene. de 2019

Overall I enjoyed the course, but it lacks structure. Some materials are assumed to be well known by the learner and surprisingly some easier ones are not. I like to see the math, but it needs more materials to support it. Most instructor's have very heavy accent and tend to speak too quickly, I find myself rewinding multiple times just to figure out what was being said. Homework's are not too difficult, and are enjoyable. Except for the last one where you need to wait for a peer review. I think this can be a flagship course with more efforts.

por Hermon A

12 de ago. de 2019

The explanation of TensorFlow is not enough and the programming homeworks have already a lot of already written (because, i would be very difficult to programming the all of the homework by ourselves in this stage of learning). I think it is better programming homeworks with examples more easy, but with more programming by ourselves.

At least, I think it is already well enough for the final evaluation, the automatic correction and then, the correction by peer only delay the evaluation.

por RJ C

26 de jun. de 2018

I could not understand what the lecturer in the second week was saying. Overall good content but awful presentation. Exercises are ridiculous, my code is working fine, but since I do not use the same function as teachers and I do not get the same result to 0.00001, I cannot pass the class. Definitely will not be renewing this class. Think twice before signing up..I am sure the guys that made the class are really smart, and the content is high quality, but overall I am disappointed.

por Juan C E

27 de feb. de 2018

The quality of some of the video session is not good, especially for RNN's. Very general, badly explained and little practical information for the practical assignments. Yor have to "learn" the material, not just look for additional information, from other sources.

The pratical assignments are note always well designed, and some are full of flaws. After many many hours of dealing with some of them, you get the impression that you've passed the assignment but not learned much.

por Carlos V

6 de oct. de 2018

The Course is good, probably should be called introduction to advance deep learning, the complexity of the assignments make you put lots of efforts around them, that is rewarding at the end, make sure you have plenty of time to dedicate to this Course, one thing the Course could improve on is to try to minimize the switch between libraries and the low-level coding with high-level coding between TF and Keras sometimes it creates confusion.