https://github.com/silviaamam/tf_hackathon
TensorFlow workshop for the Centre for Computational Chemistry
https://github.com/silviaamam/tf_hackathon
hackathon tensorflow tensorflow-tutorials
Last synced: 3 months ago
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TensorFlow workshop for the Centre for Computational Chemistry
- Host: GitHub
- URL: https://github.com/silviaamam/tf_hackathon
- Owner: SilviaAmAm
- Created: 2018-03-18T16:36:46.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-11-28T14:20:37.000Z (over 5 years ago)
- Last Synced: 2025-01-08T17:04:36.289Z (5 months ago)
- Topics: hackathon, tensorflow, tensorflow-tutorials
- Language: Python
- Homepage:
- Size: 1.13 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Glowacki Group Hackathon 2018
26th-27th of April 2018
## Before the workshop
The workshop will use python 3 and TensorFlow 1.6. You can find instructions on how to install TensorFlow [here](https://www.tensorflow.org/install/).
The powerpoint and pdf slides for the tutorial part of the Hackathon are in the [Presentation](./Presentation) folder.
## Timetable
Thursday 26th of April, Tutorial (10 - 12 am):
* Introduction to TensorFlow (presentation, ~20 min):
1. What is the point of TensorFlow
2. Comparison of Numpy and TensorFlow
3. Bulding a data flow graph
4. Running the graph
5. Basic components of a program in TensorFlow
* Playing with examples 1 (workshop, ~20 min):
1. Summing numbers
2. Linear regression
3. Quadratic function
* How to build a simple neural network (presentation, ~15 min)
1. How does a neural network work. A good reference can be found [here](http://ufldl.stanford.edu/tutorial/).
* Playing with examples 2 (workshop, ~20 min):
1. Cubic function
* Tensorboard and Dataset API (presentation, ~15 min)
Thursday 26th of April, Projects (1-5 pm):
1. Auto-encoder for picture compression:
Introductions to the theory of autoencoders and how to build one can be found [here](http://ufldl.stanford.edu/tutorial/unsupervised/Autoencoders/) and [here](https://blog.keras.io/building-autoencoders-in-keras.html).
2. "Beginner" tensorflow tutorials can be found [here](https://www.tensorflow.org/versions/r1.1/get_started/mnist/beginners).
3. Advanced tensorflow tutorials can be found [here](https://www.tensorflow.org/tutorials/). For those of you that are feeling adventurous...
Friday 27th of April:
Carry on with the Hackathon projects/tutorials.