Search Results for "visual%20scraper"
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Showing 5 open source projects for "visual%20scraper"
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Automate contact and company data extractionGenerate 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.
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math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
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HaxHexEditor is a file search system which search into multiple files (batch) with multiple definable searchstrings. The searchstrings can be specified by multiple wildcards. The search results will be exported in the HexWorkshop .HBK format
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Ocular is a spreadsheet written entirely in python. Cell contents are evaluated by python after any standard spreadsheet coordinates are parsed. This allows the full Monty from Python to be implemented in a visual environment.
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Investigation the concept of speed knowledge acquisition through speed reading and visual display. The initial version should be based on the concept provided by Dictator and should be a variable speed reader, handling TeX formatted files. Project design
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Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software.Founded in 2004, axefinance is a global market-leading software provider focused on credit risk automation for lenders looking to provide an efficient, competitive, and seamless omnichannel financing journey for all client segments (FI, Retail, Commercial, and Corporate.)
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ExoPlanet
GUI based toolkit for running common Machine Learning algorithms.
...It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model.
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