Welcome to Cogitare’s documentation!¶
Cogitare is a Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python. A friendly interface for beginners and a powerful toolset for experts.
Check the tutorials at Cogitare Tutorials.
With Cogitare, you can use classical machine learning algorithms with high performance and develop state-of-the-art models quickly.
The primary objectives of Cogitare are:
- provide an easy-to-use interface to train and evaluate models;
- provide tools to debug and analyze the model;
- provide implementations of state-of-the-art models (models for common tasks, ready to train and ready to use);
- provide ready-to-use implementations of straightforward and classical models (such as LogisticRegression);
- be compatible with models for a broad range of problems;
- be compatible with other tools (scikit-learn, etcs);
- keep growing with the community: accept as many new features as possible;
- provide a friendly interface to beginners, and powerful features for experts;
- take the best of the hardware through multi-processing and multi-threading;
- and others.
Currently, it’s a work in progress project that aims to provide a complete toolchain for machine learning and deep learning development, taking the best of cuda and multi-core processing.
Contributions are welcome!
- Sequential Model
- Sequential Data
- Async Data Loader
- Cogitare Monitor