Back to Introduction to Deep Learning

4.6

1,198 ratings

•

265 reviews

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

Jun 02, 2019

one of the best courses I have attended. clear explanation, clear examples, amazing quizzes & Programming Assignment this course is advanced level, don't enroll it if you are a new starter.

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By 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

By Ivan M

•Oct 14, 2019

Frankly speaking, I want to set 3 or 2 stars because of:

1) Many non-documented issues which I have writing code for assignments.

2) Material have been made in many foreign languages, but Russian is forgotten and it dissapointed me (hello from Moscow!)

3) Some task descriptions are not actual.

4) Coursera notebooks version is not equals github version (I checked it in GAN).

But hard to learn easy in battle, right? I learn more when try to pass Numpy NN, GAN, LSTM and etc in spite of material, English (I realise that it is very difficult task to fit a lot of material in 5/10/15 minutes. Alexander Panin tried to do it=)). It was very hard, but I did it. I realised that the authors of the course have many important projects and haven't enough time for the courses. So, I want to wish them success in their job and continue work on this course. I believe that they can do better. That's why I set 5 starts. Good luck!

By Sinan G

•Nov 08, 2019

Wide and deep range of important topics, a high level for an introduction course.

By Christhian F

•Oct 29, 2019

Very good and challenging!!

By Dalton H

•May 24, 2019

This course was great. I thought the lectures were good, and the quizzes are good at testing your knowledge, but the bets part of the course comes from the assignments. The assignments were both fun and interesting, and allowed me to try different tasks I would have been too intimidated to try otherwise (such as GANs). I really enjoyed this course.

By Evgeniy R

•Nov 07, 2017

Very practical course, provides all the necessary means for the deep learning dive. Being trained as a statistician, I used to believe I'm a bit too oldschool to do deep learning, and now look at me using keras and Tensorflow! Almost as embarrassing as your dad trying to skate.

By nishan p

•Feb 24, 2018

A good course for introducing the various concepts of Deep Learning. It neither goes too deep into the models nor taught in a blackbox way. I think it's just a mixed of both ways. The teachers were good. :)

By Michael B

•Nov 11, 2018

Excellent course which introduces the core concepts of deep learning. However, it is not for the absolute beginner. If you have a good understanding of programming in Python and have done some other introductory deep learning courses, you should be able to complete this course without too much trouble.

By Murat Ö

•May 21, 2019

It is a well prepared course which includes lots of tips and trick and theoretical background to be successful.

By Alfonso M

•Jan 31, 2019

Good course.

By Zoltan S

•Apr 08, 2018

It is fast paced. One of the best courses I have ever taken.

By 徐雨臻

•Aug 20, 2019

excellent courses

By Daniel M

•Apr 30, 2018

Challenging, educational, and tons of fun.

By Yunfei D

•Aug 05, 2018

I learnt some good ideas which can not get from other courses.

By Vladimir S

•Dec 13, 2017

Курс немного сыроват. Особенно касается задания для отличников на одной из недель, которое нельзя сабмитить. А так молодцы - курс хороший хоть и с недочетами. СПС авторам.

З.Ы. Некоторым лекторам всё-таки я бы посоветовал поработать над произношением...

By Ayush T

•Jul 26, 2018

I think this is the best course on Deep Learning on Coursera. It has flavours of various domains of Deep Learning like CNN, RNN, AutoEncoders and GAN's. The pace of this course is moderate which makes it easy to follow if you know a couple of thing about Deep Learning in advance. Definitely, this course is not for those people who are at a very initial stage or with no knowledge of learning Machine Learning. The assignments which are part of the assignment are really well chosen. This course makes you explore the subject on your own. But still the domain of Deep Learning is huge so there is still a lot to learn.

By Ezequiel A

•Aug 20, 2018

I liked this course!

By Имангулов А Б

•Jul 16, 2019

hard!

By 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.

By Richard H D

•Jul 04, 2019

Good explanation and project proposals

By Siddhartha D

•Mar 31, 2018

Course contents are good. Assignments are hard but you get to understand the intricacies of the workings of different types of neural networks and its really fun to do. There are few cases where the assignments require a GPU to work efficiently. I think Coursera should sign up with GPU cloud vendors for deep learning courses. Although peer grading process can be really helpful, I absolutely dislike it. In one instance, my assignment was marked as not runnable by one of the peers while other peers have marked it as runnable and had awarded scores for the other sections of the assignment. But, I had to resubmit the assignment in order to get the full score and it took a while for it to get reviewed as not many peers are available. In some cases, one might have to switch the session. Overall, I highly recommend the course as there's quite a lot to learn from it. Thanks.

By Vaibhav O

•Mar 17, 2019

Excellent hands on exercises to learn the basics

By Yunzhe F

•Sep 08, 2018

Most of the assignments are unclear.

By Ivan S

•Nov 11, 2018

Great introduction course

By 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

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