Search Results for "social network visualizer"

...Various built-in high-level framework integrations for both clients and servers, aiming to create a seamless experience. Authlib offers generic implementations of RFCs. Supporting a wide range of social network service connections, powered by Loginpass. Authlib is built from low level of specifications to high level of framework integrations. Security matters in Authlib. We have a section on security process at the very first begin. Authlib is created with sustainable maintainence in mind. Consider to buy a commercial plan.

Sophisticated environment for developing web-based applications. It includes lots of handy low-level components including: 1/ mySql interface, including table creation, tables as class, query as iterator 2/ html generation 3/ multi-lingual ability 4/ html form field handling 5/ etc. On top of this is a high-level framework that allows rapid development of database apps including seach/create/display/update, user navigation between related entities and much more. Included, as a...

Workshops is an open source, simple, dead-lightweight LMS (Learning Management System) application programmed in Python (version 3.8.x) with Django (version 2.2.x) web framework which main purpose is to make a standarized way to share knowledge via courses in a slide-based view in browser powered by remark javascript library, easy to create, edit, delete and show your courses using simple markdown and html if necessary. Inspired on an old project in my social labours to help share knowledge...

...MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. ...

FlightFeather's goal is "social networking for everyone". This means that anyone should have a chance to run a popular social networking site -- on minimal hardware, and without wasting bandwidth.

Motinha is a Simple Information Gathering and Network Exploitation Framework coded in Python. Here we have a bridge between the final user and the most futurists’ tools on the Internet to find juice info around any network, website, domain, company or persons and in some cases exploit some features to have fun , now let’s Shut Up And Hack!

Konfidi is a trust framework that uses topical trust values from a social network of authenticated people. When you receive an email from someone you do not know, but he/she is in the network, Konfidi will compute an inferred trust value for you.

The Pointrel System is an RDF-like triple store implemented on the Java/JVM platform, supporting related social semantic desktop applications to create, use, exchange, and organize informational resources for a reasonably joyful and secure world.

The Virtual Commons (http://commons.asu.edu) is an open software initiative devoted to computational experiments on collective action and resource governance and funded by Arizona State University's Center for Behavior, Institutions, and the Environment (http://cbie.asu.edu). NOTE: we've moved our development to GitHub at https://github.com/virtualcommons - please look for the latest versions there.

NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.

eBarter froms trades from commitments. It measures economic values without the need of a common value standard; distributes fairly the gain produced between participants and gives the preference to trades where participants have the weakest requirements.