2020-08-05 23:05:32 +02:00
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# ML4T
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This is my solution to the ML4T course exercises. The main page for the course
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is [here](http://quantsoftware.gatech.edu/Machine_Learning_for_Trading_Course).
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The page contains a link to the
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[assignments](http://quantsoftware.gatech.edu/CS7646_Spring_2020#Projects:_73.25).
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There are eight projects in total.
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2020-08-06 02:10:38 +02:00
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To set up the environment I have installed the following packages on my Linux
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Manjaro based system.
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2020-08-05 23:05:32 +02:00
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2020-08-06 02:10:38 +02:00
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```
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sudo pacman -S python-pandas --asdeps python-pandas-datareader python-numexpr \
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python-bottleneck python-jinja python-scipy python-matplotlib \
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python-numpy
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```
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2020-08-29 04:36:43 +02:00
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I am also using the wonderful
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[mplfinance](https://github.com/matplotlib/mplfinance). You can install
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mplfinance via pip and find the tutorial
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[here](https://github.com/matplotlib/mplfinance#tutorials).
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```
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pip install mplfinance --user
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```
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2020-08-06 02:10:38 +02:00
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Use unzip with the `-n` flag to extract the archives for the different
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exercises. This makes sure that you do not override any of the existing files. I
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might add a makefile to automize this later.
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```
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2020-08-07 20:06:07 +02:00
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unzip -n zips/20Spring_martingale.zip -d ./
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2020-08-29 04:36:43 +02:00
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unzip -n zips/19fall_optimize_something.zip -d ./
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2020-08-06 02:10:38 +02:00
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```
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2020-08-05 23:05:32 +02:00
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2020-08-07 20:06:07 +02:00
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# Reports
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2020-08-29 04:36:43 +02:00
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- [Report 1](./martingale/martingale.md)
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2020-09-08 03:24:45 +02:00
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- [Report 2](./optimize_something/readme.md)
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- [Report 3](#)
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2020-08-07 20:06:07 +02:00
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