- How to deploy Machine Learning/Deep Learning models to the web - Apr 5, 2021.
The full value of your deep learning models comes from enabling others to use them. Learn how to deploy your model to the web and access it as a REST API, and begin to share the power of your machine learning development with the world.
- Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API - May 15, 2018.
In this tutorial, a CNN is to be built, and trained and tested against the CIFAR10 dataset. To make the model remotely accessible, a Flask Web application is created using Python to receive an uploaded image and return its classification label using HTTP.
Pages: 1 2
- Create or machine-learn fuzzy logic rules for use with an on-line inference engine - Dec 8, 2015.
New DocAndys SaaS service supports user-created embeddable Fuzzy Logic Expert Systems. Use rule language Darl to hand-create or machine-learn rule sets from data and use them via REST interfaces.
- BABELNET 3.5, Largest Multilingual Dictionary and Semantic Network - Sep 29, 2015.
BabelNet 3.5 covers 272 languages, and offers an improved user interface, new integrated resources of Wikiquote, VerbNet, Microsoft Terminology, GeoNames, WoNeF and ImageNet, and a very large knowledge base with over 380 million semantic relations.
- Standardizing the World of Machine Learning Web Service APIs - Jul 8, 2015.
We introduce Protocols and Structures for Inference (PSI) API specification which enables delivering flexible Machine Learning by specifying how datasets, learning algorithms and predictors can be presented as web resources.
- Statistics.com courses on RESTful APIs - Feb 17, 2015.
Applying analytics to big data requires a mechanism to rapidly get and share data and RESTful APIs is the standard way doing it. Learn how to write Python code to ingest data, communicate with, and create RESTful APIs with online courses from Statistics.com.
- BabelNet 3.0, Large Multilingual Dictionary and Semantic Network - Dec 20, 2014.
BabelNet 3.0 covers 271 languages, and offers brand-new user interface, Improved accuracy of seamless integration of WordNet, Open Multilingual WordNet, Wikipedia, OmegaWiki, Wikidata and Wiktionary, around 2 billion RDF triples available via a public SPARQL endpoint.