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学生对 国立高等经济大学 提供的 Introduction to Deep Learning 的评价和反馈

4.6
1,638 个评分
377 条评论

课程概述

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...

热门审阅

DK

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

AM

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

筛选依据:

226 - Introduction to Deep Learning 的 250 个评论(共 377 个)

创建者 Krishna H

Jun 10, 2020

Exemplary!

创建者 Alex

Mar 01, 2018

Nice work.

创建者 Xiao M

Dec 19, 2017

Very gooda

创建者 Kollipaka s

May 22, 2020

very good

创建者 M A B

Feb 25, 2019

Excellent

创建者 胡哲维

Dec 23, 2018

excellent

创建者 franco p

Sep 29, 2019

Amazing!

创建者 Parag H S

Aug 13, 2019

Amazing

创建者 MAINDARGI Y R

Jul 16, 2020

Great

创建者 Имангулов А Б

Jul 16, 2019

hard!

创建者 heechan s

Sep 10, 2019

Good

创建者 Sasikumar G

Jul 20, 2018

Good

创建者 Колодин Е И

Aug 18, 2019

top

创建者 Arsenie a

Apr 05, 2018

B

创建者 Aparna S

Jan 06, 2020

The material that it is trying to cover is very good. The programming assignments are intuitive with fill in the blanks kind of approach. Finishing them and the quizzes was a breeze.

But if you are new to tensorflow and Keras and a picky like me in wanting to know exactly what is going on and how, this course is wanting details.

It does have few other minor hitches -

-It has missing links to resources (you can dig them out though)

-mistakes in slides (that they embarrassingly correct inside)

-If you care about math, it might be disappointing when you see formulae with ill-defined variables and assumptions about notations that are not discussed. If you have a background, and do simple web search you will find it out in no time though.

-

创建者 Bikhyat A

Jul 27, 2020

The course is really awesome, especially the lecturer Andrei Zimovnonv's lectures are really good. His flow, the concepts he provide, all are lucid. However, Alexander Panin's lectures are, I think quit difficult to understand. Most of the times, he suddenly delivers so fast that you can't even hear what he actually said. I think, he should work on that. And honestly, I still have lot's of confusion in the portions he covered i.e. embedding, auto-encoders, adversial networks etc. One more thing what I'd like to add is, the instructions provided in the assignment notebooks are sometime very hard to understand making me feel they're confusing and incomplete.

创建者 Arend Z

Feb 09, 2018

Very helpful to get a good basic understanding of the different types of neural networks and their application. After finishing the course, I do not yet feel confident enough to build my own neural network applications. Maybe this can be solved by having more programming assignments at 'beginner' level, before 'stepping up' the complexity.

The provided 'example' codes - that work after successful completion - serve as a good starting point to build your own neural networks.

创建者 Anselmo F

Mar 22, 2020

Very interesting course, the notebooks are very useful and all the concepts are very well motivated and explained. I just found some bugs in the course and had some problems with the explanations of week 4 and I believe week 5 lacked the explanation of some basic concepts, but all of these gaps could be filled with a research of additional material. Anyway, I recommend this even for beginners, all you need to know are derivatives and some Python basics.

创建者 Abhinav S

Apr 23, 2018

It is not an easy course, but the course projects are very nice. I really liked the RNN and CNN parts of this course very well explained and had some rigour to it.

My only complaint about the course is that it is not self contained. You will have to read up a lot more and refer to other sources on the internet to get a firm grasp of what is being taught and then go ahead to tackle the exercises.

创建者 Jay U

Jun 26, 2018

+ Instructors go into considerable theoretical depth and are very knowledgeable. + Great assignments, but can be pretty challenging+ You will learning a lot by taking this course.-Some instructors are much better than others- Instructors rely too much on slide reading. Lectures lack interactivity other than an occasional pop question.- Discussion groups are not active. Many posts go unanswered

创建者 Zhen Y

Jan 31, 2018

I found the first assignment (Week2) very difficult if you didn't have enough experience in Tensorflow to start with. Later on, the assignments became more enjoyable.

The course is more advanced than Machine Learning and DeepLearning.AI. Lots of concepts are gone through very quickly. It is not ideal if you are new to the subject. However, it covers great details in a short course.

创建者 Saptashwa B

Jan 21, 2020

Very nice course with a great project in the end. I just think this course is little too big (7 weeks) and still at times fail to cover important points in detail. I assume they are covered in the next courses of the specialization. Specially convolutional neural network for image classification requires better explanations at some part. Just my opinion though !

创建者 Juho H

Jun 25, 2020

Very challenging assignments, and unfortunately using the old version of Tensorflow. On the other hand, you really get an understanding on many things other courses skip (like the different optimizer algorithms), and the labs are very interesting. But you really need to have already fairly much experience in machine learning before tackling this one!

创建者 Ipsita S

Feb 17, 2020

As I'm familiar with deep learning I took a advanced course in order to learn new things and enhance what I already know. I have given a four star because I didn't find things new for me but I continued because the course is well structured and the assignments actually were helpful for practical learning.

Overall a good experience for me!

创建者 Emanuel P F

Jan 09, 2019

It is not a introductory course! The course provides an excellent path showing the most tools in deep learning techniques but you have to spend more time looking for additional material to supplementary this course. In general you will learn the basic about Neural Networks, Convolutional Neural Networks, and Natural Language Processing.