Machine-learning capabilities are at the heart of future technology development at Kx. Libraries are added here as they are released. Libraries are released under the Apache 2 license, and are free for all use cases, including 64-bit and commercial use.
How to set up kdb+ to create a machine-learning environment using either Anaconda, Docker or a manual build.
Natural Language Processing¶
NLP is the first module in our machine-learning suite, and manages the common functions associated with processing unstructured text. Functions for searching, clustering, keyword extraction and sentiment are included. Demonstration notebook
- Python variables and objects become q variables – and either language can act upon them.
- Python code and files can be embedded within q code.
- Python functions can be called as q functions.
Users can now install kdb+ along with our supported Python and Machine Learning libraries, embedPy and jupyterq using the popular Anaconda package-management system
JupyterQ supports Jupyter notebooks for q, providing
- Syntax highlighting, code completion and help
- Multiline input (script-like execution)
- Inline display of charts
All machine-learning libraries are:
- well documented, with understandable and useful examples
- maintained and supported by Kx on a best-efforts basis, at no cost to customers
- released under the Apache 2 license
- free for all use cases, including 64-bit and commercial use
Commercial support is available if required: please email email@example.com.