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AI-generated apps that pass security review
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Retool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
Tool to parse the commandline and configuration files.
Powerful commandline and configuration file parsing for C++, Python, Ruby and Java (others to come). This tool provides many features, such as separate treatment for options, variables, and flags, unrecognized object detection, prefixes and much more.
Video processing and computer vision library for GNU/Linux offering interfaces to do image- and video-I/O with ImageMagick/Magick++, Xine, firewire digital camera (DC1394), and video for linux (V4L2).
Note that this version of HornetsEye is deprecated. HornetsEye now is released as multiple packages on RubyGems.org. The source code is available on Github.com (see https://wedesoft.github.io/hornetseye-doc/ for more information).
Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
Managed MySQL, PostgreSQL, and SQL Databases on Google Cloud
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Hollaka Hollala is a chatbot engine and IRC bot. The chatbot engine uses a knowledge base organized in an XML file and WordNet for dictionary lookup. The IRC Bot has some WordNet- and Web-based functionality and is hot-extensible through Ruby programs.
This is a recommendation system built in ruby which is able to generate recommendations for user inputted data (a text file and a ratings matrix). It works on a hybrid model of collaborative filtering and content based filtering.
Prastava (hindi for "suggestion") - a generic open source recommendation system built entirely in ruby. This system gives recommendations to users on the basis of their past likings (ratings of items) and an item file(for content based similarity).