Comments (12)
I think the best way to get started with deep learning is determine the field that you are most interested in, such as Natural Language Processing, Computer Vision and Speech Recognition. Whenever that is determined, you try to find books, online courses or any other resources that applies deep learning for the determined field.
For me, I am interested in NLP, so, I decided to get started in deep learning by taking "Deep Learning for Natural Language Processing".
http://cs224d.stanford.edu/syllabus.html
If you haven't decided yet the field, then you can get started with the general idea of Deep Learning. You can begin with this course
https://www.coursera.org/learn/neural-networks
and this book
http://www.deeplearningbook.org/
After learning the concepts, you may need to know the libraries and programming languages that help you to implement a deep learning based project. Tensorflow, theano and keras in Python are great tools for that. This course will help you in Tensorflow https://www.udacity.com/course/deep-learning--ud730
There are some interesting blogs that write about Deep Learning, such as
http://colah.github.io/
http://www.wildml.com/
http://karpathy.github.io/
Finally, to practice more on using deep learning, you can apply its techniques in Kaggle https://www.kaggle.com/
Kaggle is a great place for practicing in Machine Learning.
from machine-learning-for-software-engineers.
http://neuralnetworksanddeeplearning.com/ is also seems good.
from machine-learning-for-software-engineers.
Tensorflow is a popular library so far for deep learning. I found this repo https://github.com/alrojo/tensorflow-tutorial very useful. For each notebook, there are resources for deep learning concepts, algorithms, then you practice and finally apply on a kaggle challenge.
from machine-learning-for-software-engineers.
Open Source Deep Learning Curriculum: http://www.deeplearningweekly.com/pages/open_source_deep_learning_curriculum
from machine-learning-for-software-engineers.
This is a good resource for starters: http://course.fast.ai/
from machine-learning-for-software-engineers.
https://github.com/ischroedi/Deep-Learning/
from machine-learning-for-software-engineers.
Deep Learning is a vast filed but this can be covered very easily if we have a good instructor in the house , so i would suggest to go for Coursera Deep Learning Specialization its the best ,just keep the trust in it and u will be the best in your field
LInk - https://www.coursera.org/specializations/deep-learning
from machine-learning-for-software-engineers.
Thank you so much!
On Mon, Oct 17, 2016 at 5:24 AM, Ahmed Hani Ibrahim <
[email protected]> wrote:
I think the best way to get started with deep learning is determine the
field that you are most interested in, such as Natural Language Processing,
Computer Vision and Speech Recognition. Whenever that is determined, you
try to find books, online courses or any other resources that applies deep
learning for the determined field.For me, I am interested in NLP, so, I decided to get started in deep
learning by taking "Deep Learning for Natural Language Processing".
http://cs224d.stanford.edu/syllabus.htmlIf you haven't decided yet the field, then you can get started with the
general idea of Deep Learning. You can begin with this course
https://www.coursera.org/learn/neural-networks
and this book
http://www.deeplearningbook.org/After learning the concepts, you may need to know the libraries and
programming languages that help you to implement a deep learning based
project. Tensorflow, theano and keras in Python are great tools for that.
This course will help you in Tensorflow https://www.udacity.com/
course/deep-learning--ud730Finally, to practice more on using deep learning, you can apply its
techniques in Kaggle https://www.kaggle.com/Kaggle is a great place for practicing in Machine Learning.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
#3 (comment),
or mute the thread
https://github.com/notifications/unsubscribe-auth/ANio0CepuSI3-C8tcqaNzm5ujttjX2BOks5q0qQagaJpZM4KX8ON
.
from machine-learning-for-software-engineers.
What do you think about this road map? http://blog.digitalmind.io/post/deep-learning.
It's not the top-down method, but it has a lot of good resources.
from machine-learning-for-software-engineers.
Here is another hot theoretical approach: https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap. But it is not suitable for everyone
from machine-learning-for-software-engineers.
I received comments from Hacker News's user annnnd for this roadmap.
For someone who has basic background knowledge in ML and wants to know more about NN and DL, my list would be:
- Neural Networks and Deep Learning (http://neuralnetworksanddeeplearning.com/) - perfect overview, go over it twice at least (the second time you will understand much of the decisions in the start)
- Tensorflow and deep learning, without a PhD (https://www.youtube.com/watch?v=sEciSlAClL8) - as much as I hate video lectures, this one was worth it; a good complement to the book above
- Theano Tutorial (http://deeplearning.net/software/theano/tutorial/index.html) - using Theano or TensorFlow takes some getting used to. I found TensorFlow documentation absolutely horrible for beginners, probably because the authors expect users to already know such frameworks. Once you learn Theano you won't have trouble with TensorFlow (if that's what you want to use).
Then there are more specific papers, but I guess those depend on the problem at hand.
from machine-learning-for-software-engineers.
Really helpful,thanks!!!!!!!
from machine-learning-for-software-engineers.
Related Issues (20)
- The new work
- Machine learning for software engineer
- Machine learning
- Call issues HOT 1
- Update resources in "Becoming an Open Source Contributor"
- Machine Learning
- Some sentences should come as quote HOT 2
- Spanish language support HOT 2
- Korean language support HOT 7
- Can you take a look at my Machine Learning Map and let me know what you think? HOT 2
- About these materials of ML HOT 1
- 我尝试翻译了一篇文章,如果可以能否提一些意见?
- Does anyone have a mind map about ML? HOT 3
- Traditional Chinese(zh-TW) language support HOT 1
- Some link die HOT 2
- Useful web rersources HOT 2
- Machine learning
- New youtube channel (ML resource)
- Guia Ml HOT 1
- Hello Kaggle! It is a guide for new kaggler
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from machine-learning-for-software-engineers.