提交 54bc197e authored 作者: James Bergstra's avatar James Bergstra

revising cifar10SC intro

上级 add20871
...@@ -15,51 +15,58 @@ Day 1 ...@@ -15,51 +15,58 @@ Day 1
* Show of hands - what is your background? * Show of hands - what is your background?
* Overview/Motivation * Python & Numpy in a nutshell
* Theano basics
* Quick tour through Deep Learning Tutorials (think about projects)
.. :
day 1:
I think that I could cover those 2 pages:
* http://deeplearning.net/software/theano/hpcs2011_tutorial/introduction.html
* http://deeplearning.net/software/theano/hpcs2011_tutorial/theano.html
That include:
simple example
linear regression example with shared var
theano flags
grad detail
Symbolic variables
gpu
benchmarck
* python/numpy crash course Day 2
-----
* Theano beggining * Loop/Condition in Theano (10-20m)
* Example with recent ML models (DLT) * Propose/discuss projects
day 1: * Form groups and start projects!
I think that I could cover those 2 pages:
* http://deeplearning.net/software/theano/hpcs2011_tutorial/introduction.html
* http://deeplearning.net/software/theano/hpcs2011_tutorial/theano.html
That include:
simple example
linear regression example with shared var
theano flags
grad detail
Symbolic variables
gpu
benchmarck
Day 2 Day 3
----- -----
* Day 2: * Advanced Theano (30 minutes)
* Loop/Condition in Theano (10-20m)
* Propose/discuss projects
* For groups and start projects!
Day 3 * Debugging, profiling, compilation pipeline
-----
* Day 3: * Projects / General hacking / code-sprinting.
* Advanced Theano(30 minutes)
* Debuging, profiling, compilation pipeline, inplace optimization
* Projects / General hacking / code-sprinting.
Day 4 Day 4
----- -----
* Day 4: *You choose* (we can split the group) * *You choose* (we can split the group)
* Extending Theano or
* How to wrap code in an op * Extending Theano
* How to use pycuda code in Theano
* Projects / General hacking / code-sprinting.
* How to write an Op
* How to use pycuda code in Theano
* Projects / General hacking / code-sprinting.
Note - the schedule here is a guideline.
We can adapt it in reponse to developments in the hands-on work.
The point is for you to learn something about the practice of machine
learning.
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