Doomsday is an emerging deep learning framework written in Scala. Aimed at offering seamless numerical computations with the power of Scala, it leverages the Breeze library to provide high-speed numerical and linear algebraic operations. Please note that this library is still under development, and contributions or feedback are highly appreciated.
- SDK: 1.8
- Scala Version: 3.1.3
- Breeze: 2.1.0
- Breeze - A library for numerical processing and scientific computing in Scala.
- Clone the repository:
git clone https://github.com/rxxuzi/doomsday.git- Add Doomsday to your sbt project:
In your build.sbt file, add the following dependency:
libraryDependencies += "com.rxxuzi" %% "doomsday" % "latest.version"(Replace "latest.version" with the current version of Doomsday.)
- Using the library:
After setting up the dependency, you can start using Doomsday in your project:
import doomsday.core._
import doomsday.function._
import doomsday.models._
import doomsday.dataset._
import doomsday.optimizers._Sample code can be found in example.
You can now utilize all the functionalities provided by Doomsday.
- Flexibility: Design and train custom neural network architectures tailored to your needs.
- Optimizers: Multiple optimization algorithms available like SGD, Adam, RMSprop, etc.
- Loss Functions: A variety of loss functions to choose from, including MSE, Cross-Entropy, and more.
- Regularization Techniques: Support for techniques like Dropout, Batch Normalization, and L1/L2 regularization.
- Datasets: Built-in utilities to handle and preprocess datasets for machine learning tasks.
- Model Evaluation: Tools for evaluating model performance using metrics like accuracy, precision, recall, etc.
- Functional API: Leverage the power of Scala's functional programming capabilities for more expressive model design.
For detailed usage instructions, troubleshooting, and more, check out our documentation in the document folder.
This project is licensed under the MIT License. For more details, see the LICENSE file.