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Learner Reviews & Feedback for Introduction to Deep Learning by National Research University Higher School of Economics

4.6
stars
1,691 ratings
394 reviews

About the Course

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...

Top reviews

DK
Sep 19, 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

TP
Aug 8, 2020

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.

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376 - 392 of 392 Reviews for Introduction to Deep Learning

By Dulat A

Dec 17, 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.

By Peter

Jan 18, 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..

By Aswin R

Mar 13, 2019

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

By Nathan N

Mar 16, 2020

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

By Robert P M

Jul 18, 2020

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

By Mohit K

Sep 7, 2018

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

By Nick

Feb 22, 2018

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

By Roberto M P

Jan 27, 2018

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

By Aman T

Jan 3, 2021

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

By Xiaowei X

Aug 11, 2019

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

By 史永新

Jun 17, 2020

the test is too difficult to make me give up

By Herbert D

Mar 4, 2018

This has to be the worst course on Coursera.

By Jiahua F

Oct 13, 2020

The code in github doesn't work

By NIMA S

Sep 6, 2020

The English is terrible!

By Philip P

Nov 3, 2019

Out dated

By MANEESH K 2 C A

Dec 1, 2020

Bad

By ADEL S A A

Jun 11, 2020

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