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

1,844 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:

Principales reseñas

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

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

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401 - 425 de 429 revisiones para Introduction to Deep Learning

por Reza S

12 de feb. de 2021

While trying to be objective, I beleive the only credit this course takes is the extensive syllabus. Otherwise the lectures were terrible and it was almost impossible to follow any subject just by leaning to the course material. At some point I ended up muting the videos and focused on subtitles only. Pedagogically it wasn't design to "teach" so to say, and I practically ended up googling most of the topics so I can graduate this course!

por Stefano C

6 de ene. de 2018

The course has a high potential, with large content and expert instructors. However, you soon realise that the content is indeed too large, and it's never covered with enough details and examples. The most disappointing part, however, is the assignments: the topics covered are too advanced and, as a matter of fact, the learner is only given the chance to implement a tiny part of it.

por Sergio A G P

8 de jul. de 2020

I found this course not to be a good introduction to deep learning. It never explained well how to use Tensorflow for even easy things. There was a lot of topics covered, which made the course very shallow. As an introduction, it would have been great to know how to de easy things well, instead of checking lots of topics and not knowing how to fully implement them.

por Caio A A O

27 de nov. de 2017

It started great, but became a bit too shallow. There's also little to no support from instructors, even when there are bugs.

por Tanvi

14 de jul. de 2020

Language problem ,no clear instructions were given for the assignments(Notebook) and no proper reply of Discussion form.

por raghuveer n

26 de dic. de 2017

The accent is very hard to understand and the quality of the recording is not good

por Marina Z

7 de jul. de 2020

Worst ever course on Coursera. The lectures are actually well-prepared. The programming homework assignments, however, do not meet the technical requirements of Coursera in terms of dataset volume and the time needed to run the training of the models. It's pain in the bottom to train a model as asked in the course. To transfer the notebooks to Colab to train the models on Google servers is connected to many, many, many hours of additional work to rewrite the scripts. I will not finish this course and I would not suggest to begin with, unless you have nothing to do in this world except to lose your time on the improvement of the assignments.

por Fereydoon V

11 de nov. de 2017

This low-quality course sucks miserably! I still can't believe that this course has really been approved by Coursera, or perhaps Russians have compromised Coursera too?! Not only the extremely heavy accent of so-called "lecturers" makes it impossible to follow what the hell they're talking about, but also the course construction and the explanations' track lack the bare minimum of pedagogical/instructional design. These folks could have taught this course in Russian, at least it would have been usable for Russian folks!

por Akshay N

22 de dic. de 2017

Not a good course.

The lectures are rushed through. At one point towards the end of week one, the lecturer just reads out the mathematical formulae on gradient descent extensions, without giving any background on their interpretation, or any examples.The number of notations used are too many to keep track of.

There are no instructions available on how to tackle assignments in Python (nor any mention of Python language as a pre-requisite).

por Scott B

12 de jun. de 2019

This course is very poorly designed. The lectures are insufferable, and absolutely zero supplemental content is provided that would make it actually possible to engage in the material in any meaningful way beyond suffering through the prattle and drone of recitation of mathematical concepts. Very disappointing.

por Eduardo P

19 de ago. de 2021

S​till using tensorflow 1.2. I was unable to run week3 excercises in local, directly or through docker. Colab has not working. After wasting an increadible amount of time will quit the whole specialization. Very disapointing that code is not maintained / updated.

por Dulat A

17 de dic. de 2017

Quality of lectures were totally disapointing. I watched previous courses from Yandex, which were taught on Russian, and they were much better. At some points, lectures even cannot explain what they want to say. I feel like Yandex have stolen 50$ from me.

por Peter

18 de ene. de 2018

Not all teachers speak english well enough. You need to be skilled python, tensorflow, karas developer. They dont explain the algorithms very well and you dont have a text book to look it up yourself..

por Aswin R

13 de mar. de 2019

Very peripheral teaching. Unable to understand anything from the touch points being covered. Assignments are not at all matching with the course contents.

por Nathan N

16 de mar. de 2020

Quizzes are not translated to English well, and instructors are not active on the discussion forums.

por Robert M

18 de jul. de 2020

The tensorflow sections are no longer relevant and nobody answers questions about the material.

por Mohit K

7 de sep. de 2018

This course goes over my head. I found this course 'callous'. Doesn't care about my learning!

por Nick

22 de feb. de 2018

Awful. Questions unclear, lecturers struggle with basic english, and typos are everywhere

por Roberto M P

27 de ene. de 2018

The lecturer is really bad, he is not clear and his explanations are shallow and vague.

por Deleted A

3 de ene. de 2021

Course was made unnecessarily complex , it could be explained in a simpler manner.

por Xiaowei X

11 de ago. de 2019

The instructions are often unclear and the ipynb files often does not even run.

por krishnaraju

20 de abr. de 2021

assignments can't be submitted and no instructions were given how to submit it

por 史永新

17 de jun. de 2020

the test is too difficult to make me give up

por Herbert D

4 de mar. de 2018

This has to be the worst course on Coursera.

por Jiahua F

13 de oct. de 2020

The code in github doesn't work