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MXNet vs ScalaNLP: What are the differences?
Developers describe MXNet as "A flexible and efficient library for deep learning". A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. On the other hand, ScalaNLP is detailed as "A suite of machine learning and numerical computing libraries". ScalaNLP is a suite of machine learning and numerical computing libraries.
MXNet and ScalaNLP can be categorized as "Machine Learning" tools.
Some of the features offered by MXNet are:
- Lightweight
- Portable
- Flexible distributed/Mobile deep learning
On the other hand, ScalaNLP provides the following key features:
- ScalaNLP is the umbrella project for several libraries:
- Breeze is a set of libraries for machine learning and numerical computing
- Epic is a high-performance statistical parser and structured prediction library
MXNet and ScalaNLP are both open source tools. MXNet with 17.5K GitHub stars and 6.21K forks on GitHub appears to be more popular than ScalaNLP with 2.93K GitHub stars and 674 GitHub forks.
Pros of MXNet
- User friendly2