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Showing 6 open source projects for "python data analysis"
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Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum KnightCLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
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The Most Powerful Software Platform for EHSQ and ESG ManagementChoose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
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Calculation of camshafts - allows to define a camshaft profile on the set trajectory which should provide the given mechanism. The trajectory can be set graphically, co-ordinates or function.
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Libraries, documentation, examples & drivers for Eagle Technology South Africa's Data Acquisition products. These include ISA, PCI, PCI Express, USB, Serial & Ethernet. Supported languages will be C/C++, JAVA, Perl, Python.
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A project to host code developed for the Microtransat challenge, a race between autonomous sailing robots. This project is intended for both supporting code such as tracking systems and robot control systems or parts of robot control systems.
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This is the public icram.de code repository filled with code/code-snippets and other useful stuff.
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Field Sales+ for MS Dynamics 365 and SalesforceBring Dynamics 365 and Salesforce wherever you go with Resco’s solution. With powerful offline features and reliable data syncing, your team can access CRM data on mobile devices anytime, anywhere. This saves time, cuts errors, and speeds up customer visits.
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Concurrent vision processing system; Toolkit for easy implementation of software concurrent vision processing sub-system. Aimed at robotic applications w/best effort realtime. System includes: capture,processing and displaying.
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UGLi ML: The Undirected Graphical Library for Machine Learning. Easy, agile learning and inference from structured/relational data using Markov Networks and Conditional Random Fields.
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