### TASK
- Implement a neural network in a low-level programming language (C/C++/Java/Rust) without the use of advanced libraries or frameworks.
- Train it on the supplied Fashion-MNIST dataset using a backpropagation algorithm.
### REQUIREMENTS
- Your solution must follow the project template and must be runnable on the Aisa server.
- Your solution must achieve at least 88% accuracy on the test set.
- Your solution must finish within 30 minutes. (parse inputs, train, evaluate, export results.)
- Your solution must contain a runnable script called `run.sh` (not `run`, not `RUN.sh`, not `run.exe` etc.) which compiles and executes your code (and exports the results).
- Your solution must output two files to the root project directory:
(next to `example_test_predictions.csv` file):
- `train_predictions.csv` - your network predictions for the train set.
- `test_predictions.csv` - your network predictions for the test set.
- The format of these files has to be the same as the supplied training/testing labels:
- One prediction per line.
- Prediction for i-th input vector (ordered by the input .csv file) must be on i-th line in the associated output file.
- Each prediction is a single integer 0 - 9.
- Replace the first line of this file with UČOs and names (UČO - код студента с 6 цифер)
По цене рассмотрю Ваше предложения.
Applications 2
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C++ и Java это совсем не низукоуровневый язык. Вот С если не C77 еще соотвествует. То есть если вы потом для скорости его собираетесь сунуть в ядро оса, то про C++ лучше забыть, а Java вообще никаким боком не подходит
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