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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.
...See our YouTube channel for tutorial videos via the homepage.
The applications are all built out of a uniform user-interface framework that provides a very high level (Qt) interface to powerful image processing and scientific visualisation algorithms from the Insight Toolkit (ITK) and Visualisation Toolkit (VTK). The framework allows one to build stand-alone medical imaging applications quickly and easily.
MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users.
* More info + downloads: https://mlpack.org
* Git repo: https://github.com/mlpack/mlpack
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.
openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical userinterface, a web service interface and an API for Python.
Total Network Visibility for Network Engineers and IT Managers
Network monitoring and troubleshooting is hard. TotalView makes it easy.
This means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
Library written in C with Python API for IPv6 networking
This project is a rewritten of an initial project that I've called GLUE and created in 2005.
I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3
The library has to be build as a simple Python extension
using >python setup.py install
and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol.
The architecture of the code is based on brain architecture.
Will put an IPv6 adress active available as soon as...
Compares botnet detection methods by computing the error metrics by reading the labels on a NetFlow file. The original NetFlow should have a new column for the ground-truth label, and a new column with the prediction label for each botnet detection method.
This program computes all the error metrics (TPR, TNR, FPR, FNR, Precision, Accuracy, ErrorRate, FMeasure1, FMeasure2, FMeasure0.5) and output the comparison results. It also ouputs a png plot.
The program can compare in a...
A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.
A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
Yeastar: Business Phone System and Unified Communications
Go beyond just a PBX with all communications integrated as one.
User-friendly, optimized, and scalable, the Yeastar P-Series Phone System redefines business connectivity by bringing together calling, meetings, omnichannel messaging, and integrations in one simple platform—removing the limitations of distance, platforms, and systems.
Signal Processing and Classification Environment in Python using YAML
...Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical userinterface.
For obtaining a zip file of the current state use: https://github.com/pyspace/pyspace/archive/master.zip