Introduction to Deep Learning(으)로 돌아가기

4.6

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347개의 리뷰

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...

Sep 20, 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

May 29, 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

필터링 기준:

교육 기관: Akash S

•Mar 26, 2018

Great course! The faculty does an excellent job in explaining some difficult to understand concepts. The discussion forum is very active and the course community is helpful.

교육 기관: Frank F

•Jul 31, 2018

Finally a Course that does more than introducing the topic, but helps you in your every practice of deep learning modelling. Awesome! Looking forward to much more to come!

교육 기관: Timo

•May 30, 2019

Definitely great course!

(Was more interested in the math than the acutal "doing" of the programming, so I sometimes found the exercises a little enerving... :) )

교육 기관: Jens R

•Sep 02, 2019

I learned a lot. I had a tiny typo in the last exercise, which took most of my time. But searching for this mistake was probably the time I learnt the most ;).

교육 기관: Hamel H

•Dec 29, 2017

This is amazing content. The instructors have a really good sense of humor which you can detect if you are paying attention, this makes the course really fun.

교육 기관: Simon G

•Mar 20, 2019

I really liked, that you are able to clone the repositories directly do work locally on the notebooks and therefore providing a much more stable environment!

교육 기관: Saket G

•Jun 17, 2018

Challenging and motivating, it is not self sufficient but its ok to see some resources on Internet.Always excited to study this.Thanks to all teachers...!!

교육 기관: Zhanpeng H

•Jan 05, 2018

This is the best course that I have taken so far about deep learning on Coursera. It contains nice explanations about different types of neural networks.

교육 기관: Hussein N

•Nov 03, 2019

I really enjoyed this course and how practical it is. It was super exciting to make the a practical application with transfer learning only after 4 weeks

교육 기관: ashesh g m

•May 09, 2019

Its much more informative than the title suggests. A good course to take for someone who already knows basics/theoretical knowledge of machine learning.

교육 기관: Pun C S

•Oct 18, 2019

Quite In depth introduction on Deep learning. But you need to have a solid background on python and machine learning in order to catch up the materials

교육 기관: Cristhian J P S

•Jul 29, 2019

It's really helpfull and I've learn differents architectures of deep learnning. I'm going to continue with other course to practices these courses.

교육 기관: Гридасов И И

•Feb 07, 2019

The best course that I've ever seen. It gives wide and deep understanding of whatever in deep learning. I strongly recommended this course to you.

교육 기관: LOKESH J

•May 21, 2020

Excellent teachers but at time the pronounciation wasn't clear. Could be augmented by documentation. May be it is already there but didn't see it

교육 기관: Harish K B

•Jun 22, 2020

Great Course blended with real time problem solving. Loved the time with Coursera Notebook even-though its a bit hard. Thanks to all trainers.

교육 기관: Debabrata A K S

•Feb 19, 2020

It was tough and challenging but achievable. Great contents and learning materials. Instructor are good, videos are well paced too. Thanks

교육 기관: Eugene I

•Aug 29, 2018

Thank you guys for replacing some lectures. As for me, at present, the course is one of the best courses in this specialization.

교육 기관: Amit K

•May 25, 2020

This course teaches you introduction to deep learning which other courses consider as advanced deep learning. Very Very Useful.

교육 기관: Ahmed N

•Apr 23, 2018

It is great and rich contents i studied machine learning a lot and this one is very useful and beneficial to me thanks a lot.

교육 기관: Eric

•Feb 05, 2019

An advanced class for overview for deep learning. A very wide range of the usages will let you think what you have learnt.

교육 기관: SAHIR S

•Mar 08, 2018

An really good introduction to Deep Learning. I think that this course is for students already familar with eep Learning

교육 기관: Isaiah O M

•Jan 15, 2019

The course compels you to work on the solutions and hence expose you to hand-on that are very vital for understanding

교육 기관: Raman K

•Jun 25, 2018

Great course, very deep understanding of deep learning, things I had no idea of and things I always needed are there.

교육 기관: Ishwar N

•Jun 30, 2020

Excellent course with lot of Maths required for deep learning and also covering advanced topics. Highly recommended.

교육 기관: Amoghavarsha B

•Feb 02, 2020

It's a very hands on course. Lots of programming assignments which really helps improve our programming skills.