Just watch the video and don't do it. You may have taken a fake course , Li Feifei's famous computer vision work Stanford CS231n Detailed explanation of the work !
Big data digest works
I didn't really learn it after watching the video , More important is to do homework , Hands on practice , discuss , So that we can really master what we have learned . After watching Stanford CS231n Open class of , Don't you think it's enough ? Let's write the code with the abstract bacteria !
On deep learning and computer vision , I have to mention ImageNet And its creators , Associate Professor, Department of computer science, Stanford University ,Google Cloud
Li Feifei, chief scientist of artificial intelligence and machine learning team . And her famous work , Stanford University Courses 《 Deep learning and computer vision 》 Since opening videos and assignments , It also benefits a group of people who are interested in computer vision IT Practitioners .
Let's take a look at an Internet recruitment platform IT Salary comparison with visual Algorithm Engineer :
And there are so many courses in deep learning and computer vision , Why do abstract bacteria recommend it ?
first , This course is a classic course of computer vision , It's set up by Professor Li Feifei, a big guy from Stanford, a world famous university , Is it free to watch the study course !!!
secondly , Reasonable arrangement of course content , from the shallower to the deeper . It mainly introduces deep learning （ Especially convolutional neural network and its related framework ） Application in the field of computer vision , The content covers the specific structure and training application details of various neural networks , And for large-scale image recognition , Object positioning , Object detection , Image style migration , Image understanding description and video content recognition . From a simple cifar10 Datasets and the simplest KNN Algorithm Introduction , Slowly introduce knowledge points related to deep learning . such as dropout,batchnormalization etc. . Finally, some classic examples of deep learning are introduced , such as RNNs,
LSTMs ,GAN etc. .
last , It's also a reason why the editor should emphasize , Chinese characters embedded in video course ! you 're right , Despite the majority IT Practitioners have basic English level , But to understand such a profound course , It still takes a lot of effort . And Chinese video not only needs high English level , More in-depth learning professional ability is needed .
Big data abstracts and pattern recognition Laboratory of Beijing University of Posts and telecommunications have jointly completed this huge project !
Time consuming 6 Months （ from 2016 year 9 month -2017 year 2 month ）! Thank you very much , Crazy fight for you call.
The hard work of the staff of the subtitle localization team has also paid off handsomely , Since the launch of the course , The number of plays in Netease cloud class has reached today 77790 second , Course rating up to 5 Stars ,5 Oh ! Big data digest also reaps a large number of true love fans of the course , You are also looking forward to asking about CS224 What about the course .
by the way , Are there any students who haven't had time to study this classic course ? Poke the link below to learn !
Everyone's enthusiasm for learning is also very high , All kinds of wonderful notes ：
It seems that there are a lot of big guys studying this course , If you think you're going to get started with machine vision after class , Then you are too simple . Do homework after class , You still need to type the code . But how to deal with difficulties in doing homework ? What to do without reference to the answer ?
Abstract bacteria heard everyone's voice , Also invited a group of front-line employees , Sacrifice rest time , Study course assignments by hand , And arranged the complete notes of the course assignment .
Note writer and proofreader's knowledge about each problem in the assignment , They all explained the relevant knowledge points . The content not only involves some knowledge in the course , There are also the experience of the front-line employees and the expansion of knowledge points . We can carry out practical operation for each topic , To deepen the understanding of each question .
For example, for assignment1 In Q2, Our volunteer students gave such detailed answers ：
To help you finish your homework , Note writer and proofreader give complete code of each question as reference , And the code has detailed comments , Is it super ?
How can I get such wonderful notes ? Here is a link to the first issue of the assignment notes
Big data digest Netease cloud course column ：
Big data digest CSDN special column ：
Big data digest GitHub special column ：
We will release all the work in batches according to the progress , Please keep your attention on big data digest .
last , Let's thank the staff for this assignment , It's your selfless giving , Let more readers enjoy this achievement .
All authors ： Guo Chengkun View freedom and subdue the devil Fanli SlyneD potato MoreZheng Zhang Lijun
Proofread ： Molly Guo Chengkun
Check and verification by the head school ： Han Xiaoyang
Copywriting ： Feng Xiaoli
【 Today's machine learning concepts 】
Have a Great Definition
Phase I volunteers