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

4.5
звезд
Оценки: 1,830
•
Рецензии: 428

О курсе

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....

Лучшие рецензии

DK
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

AM
28 мая 2020 г.

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

Фильтр по:

176–200 из 426 отзывов о курсе Introduction to Deep Learning

автор: Ravindran M

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4 дек. 2018 г.

Good course. More detailed lectures may have been helpful.

автор: Subham T 1

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21 февр. 2018 г.

Nice course with all the concepts explained in a lucid way

автор: Udith D B H

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12 мар. 2020 г.

Excellent course which expects much practical knowledge.

автор: MEET S

•
18 апр. 2020 г.

Really useful to learn the basics of Deep Learning.

автор: Debasis U

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3 июля 2019 г.

I surely have learned a lot from the course, thanks

автор: Mohammed S E

•
19 апр. 2019 г.

very detailed , clear and to the point , i loved it

автор: Marcos S

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26 июня 2021 г.

t​otally recommended! robust and clear foundations

автор: Samuel R

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12 авг. 2019 г.

Great lectures and homeworks.They were challenging

автор: zhaoyulai

•
19 июля 2018 г.

课程不错, 但英语听不懂, Inception Fine-tune难度比较大, 运行耗时间且电脑发热

автор: Eyvaz N

•
8 мар. 2021 г.

The best intro to Deep Learning I have ever seen

автор: Vaibhav O

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17 мар. 2019 г.

Excellent hands on exercises to learn the basics

автор: Xin Q

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8 окт. 2019 г.

A really nice course as an introduction to DL.

автор: Tom M

•
11 мая 2018 г.

Fun course that teaches some very cool topics.

автор: Yu C

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11 июля 2020 г.

Clearly presented with desirable formal rigor

автор: Faris G

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8 июня 2018 г.

Really inspired me to continue deep learning.

автор: Aditya N J

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27 сент. 2020 г.

Awesome course . A must recommended for all

автор: Bharath R R

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20 мая 2020 г.

Great Course with good programing Excercise

автор: RLee

•
26 мар. 2019 г.

A very comprehensive "introduction" course!

автор: Firas B

•
26 нояб. 2018 г.

One of the best courses of deep learning !!

автор: Arturo O A

•
22 авг. 2018 г.

Really great course, I highly recommend it!

автор: Biswa s

•
7 янв. 2018 г.

Good Introduction. The assignments are good

автор: Jayesh G

•
24 июля 2019 г.

Nice course....refreshed a lot of concepts

автор: Daniel M

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30 апр. 2018 г.

Challenging, educational, and tons of fun.

автор: Лупашин Е И

•
2 апр. 2021 г.

топ курс спасибо любимой ВШЭ за него!!!

автор: sanghoon.lee1@kbfg.com

•
27 окт. 2020 г.

I like this lecture. thank you so much.

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