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csknow's Introduction

CSKnow

This project is my research on understanding player behavior in video games. The key components of the project are

analytics

The C++ code for implementing the bots, the analytics database querying demo files, and the server sending these queries to the web visualization.

demo_generator

The docker config files and configurations for running CSGO servers in docker containers, thus generating demos to analyze from bots

demo_parser

The golang demo parser. This parser uploads CSV results to AWS S3 by default.

download_s3_csvs

Download parsed demos' CSVs to the local_data folder. The analytics code reads the CSVs out of the local_data folder.

web_vis

The front-end code for visualizing queries computed by the analytics database.

csknow's People

Contributors

david-durst avatar shacklettbp avatar

Stargazers

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Watchers

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csknow's Issues

Comments from a squirrel

L119: Change to AdamW or Adam (less need to tune LR)

L85: no relus after final layer

L95: check docs to see if you are applying softmax twice by accident from nn.CrossEntropy

cross_entropy and cross_entropy_with_logits (check L119)
https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html

loss_fn = nn.CrossEntropyLoss()

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