Showing 5 open source projects for "deep"

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  • 1
    dlib

    dlib

    Toolkit for making machine learning and data analysis applications

    Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is...
    Downloads: 4 This Week
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  • 2
    Rust Data Analysis

    Rust Data Analysis

    Rust for data analysis encyclopedia (WIP)

    Welcome to the Rust Data Analysis repository! This collection of Jupyter notebooks provides a comprehensive exploration of data analysis using Rust. Powered by a Rust kernel, these notebooks allow you to dive deep into the realm of data analysis, leveraging the capabilities of the Rust programming language. With the help of various Rust libraries, such as ndarray, plotters, and more, you'll be able to extract valuable insights from different datasets with ease.
    Downloads: 0 This Week
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  • 3
    F1 Race Replay

    F1 Race Replay

    An interactive Formula 1 race visualisation and data analysis tool

    ...Users can scrub through time, jump between cars, and overlay performance graphs such as speed, sector times, and gap differentials to evaluate performance trends across laps. This deep dive capability turns passive viewing into active exploration, empowering enthusiasts and professionals to discover insights usually hidden in raw data. The viewer also supports annotations and bookmark capabilities so users can mark moments of interest for future review or comparison.
    Downloads: 2 This Week
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  • 4
    IoTDB

    IoTDB

    Apache IoTDB

    Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. In the scene of factories, there are tens of devices under LAN network. IoTDB can be installed on a local controller server in the factory to receive data from those devices. ...
    Downloads: 1 This Week
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    Build Agents and Models on One Platform

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  • 5

    BriPy

    A BRIC-seq data analysis package written in Python.

    -What is BRIC-seq? BRIC-seq, short for 5'-bromo-uridine (BrU) immunoprecipitation chase-deep sequencing analysis, is a novel method in Next Generation Sequencing (NGS) to determine the RNA stability of each transcript. It employs metabolic labeling by BrU of newly synthesized RNAs to chase chronological decreases of BrU-labeled RNA (Pulse-chase labeling), followed by immunoprecipitation with antibody for BrU, construction of cRNA library for High-throughput sequencing and computational data analysis. ...
    Downloads: 0 This Week
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