Abstract
There are many excellent toolkits which provide support for developing machine learning software in Python, R, Matlab, and similar environments. Dlib-ml is an open source library, targeted at both engineers and research scientists, which aims to provide a similarly rich environment for developing machine learning software in the C++ language. Towards this end, dlib-ml contains an extensible linear algebra toolkit with built in BLAS support. It also houses implementations of algorithms for performing inference in Bayesian networks and kernel-based methods for classification, regression, clustering, anomaly detection, and feature ranking. To enable easy use of these tools, the entire library has been developed…
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2,921
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- FWCI
- 5.00
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Authors
1Topics & keywords
Topics
Keywords
- Computer science
- Python (programming language)
- Debugging
- Machine learning
- Cluster analysis
- Implementation
- Programming language
- Artificial intelligence
UN Sustainable Development Goals
- Industry, innovation and infrastructure
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