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+/q to create a machine-learning environment using either Anaconda, Docker or a manual build.
Users can now install kdb+/q along with our supported Python and Machine Learning libraries, embedPy and JupyterQ using the popular Anaconda package-management system
EmbedPy loads Python into kdb+/q, allowing access to a rich ecosystem of libraries such as scikit-learn, tensorflow and pytorch.
- 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.
JupyterQ supports Jupyter notebooks for q, providing
- Syntax highlighting, code completion and help
- Multiline input (script-like execution)
- Inline display of charts
Machine Learning Toolkit¶
The Machine Learning Toolkit is at the core of kdb+/q centered machine-learning functionality. This library contains functions that cover the following areas.
- Accuracy metrics to test the performance of constructed machine-learning models.
- Pre-processing data prior to the application of machine-learning algorithms.
- An implementation of the FRESH algorithm for feature extraction and selection on structured time series data.
- Utility functions which are useful in many machine-learning applications but do not fall within the other sections of the toolkit.
The library is available here.
Natural Language Processing¶
NLP was the first module within the machine-learning suite, it manages the common functions associated with processing unstructured text. Functions for searching, clustering, keyword extraction and sentiment are included in the library, available here.
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.