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Automate contact and company data extraction
Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.
Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
The goal of this project is to investigate optimal ways to do genre classification for the ten indigenous South African languages. Funded by Dept of Arts and Culture of the SA Government.
http://www.trifonius.co.za/projects/genre-classification
Research tool for interactive training of artificial neural networks.
BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.
Featurama is a library that implements various sequence-labeling algorithms. Currently Michael Collins' averaged perceptron algorithm is fully implemented.
Lightspeed Golf is all-in-one golf course management software to help courses simplify operations, drive revenue and deliver amazing golf experiences.
From tee sheet management, point of sale and payment processing to marketing, automation, reporting and more—Lightspeed is built for the pro shop, restaurant, back office, beverage cart and beyond.
BCAR is a library for the associative classification, which denotes "Boosting
Class Association Rules". BCAR provides a general tool for classification tasks
with various types of input data.
openEAR is the Munich Open-Source Emotion and Affect Recognition Toolkit developed at the Technische Universität München (TUM). It provides efficient (audio) feature extraction algorithms implemented in C++, classfiers, and pre-trained models on well-known emotion databases. It is now maintained and supported by audEERING. Updates will follow soon.