CONTEST Telegram 349
Telegram ML Competition, Round 2: Submissions

ContestBot is now ready to accept submissions for the Telegram ML Competition, Round 2.

Start the bot, choose “ML Competition”, answer the bot’s questions, then send:
- A ZIP-archive with the following structure:

submission.zip
-> libtglang.so - shared library with interface described in tglang.h (obligatory)
-> src - folder with the app's source code (obligatory)
-> train - folder with the source code and datasets used to train the model if any (obligatory)
-> README.md - short description of the solution (obligatory)
-> resources - folder with additional files which your library requires to work (please use relative paths to access them) (optional)
-> deb-packages.txt - a text file with line-break separated debian package names of all external dependencies (optional)


Q: My archive size exceeds 2 GB.
A: You may provide a link to the datasets. In this case make sure the 'train' folder contains the source code and a link to your datasets.

For further details, please refer to the contest documentation.



tgoop.com/contest/349
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Telegram ML Competition, Round 2: Submissions

ContestBot is now ready to accept submissions for the Telegram ML Competition, Round 2.

Start the bot, choose “ML Competition”, answer the bot’s questions, then send:
- A ZIP-archive with the following structure:

submission.zip
-> libtglang.so - shared library with interface described in tglang.h (obligatory)
-> src - folder with the app's source code (obligatory)
-> train - folder with the source code and datasets used to train the model if any (obligatory)
-> README.md - short description of the solution (obligatory)
-> resources - folder with additional files which your library requires to work (please use relative paths to access them) (optional)
-> deb-packages.txt - a text file with line-break separated debian package names of all external dependencies (optional)


Q: My archive size exceeds 2 GB.
A: You may provide a link to the datasets. In this case make sure the 'train' folder contains the source code and a link to your datasets.

For further details, please refer to the contest documentation.

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