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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users.
* More info + downloads: https://mlpack.org
* Git repo: https://github.com/mlpack/mlpack
Caffe2 is a lightweight, modular, and scalable deep learning framework
...In many ways Caffe2 is an un-framework because it is so flexible and modular. The original Caffe framework was useful for large-scale product use cases, especially with its unparalleled performance and well tested C++ codebase. Caffe has some design choices that are inherited from its original use case: conventional CNN applications.
BCAR is a library for the associative classification, which denotes "Boosting
Class Association Rules". BCAR provides a general tool for classification tasks
with various types of input data.
A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers.
There are three libraries in this opensource set.
- Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms.
- Monk Object Detection -...