Showing 7 open source projects for "memory"

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  • 1
    POCO

    POCO

    Cross-platform C++ libraries for building network applications

    The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++...
    Downloads: 9 This Week
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  • 2
    Pandas Profiling

    Pandas Profiling

    Create HTML profiling reports from pandas DataFrame objects

    ...File sizes, creation dates, dimensions, indication of truncated images and existance of EXIF metadata. Mostly global details about the dataset (number of records, number of variables, overall missigness and duplicates, memory footprint). Comprehensive and automatic list of potential data quality issues (high correlation, skewness, uniformity, zeros, missing values, constant values, between others).
    Downloads: 4 This Week
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  • 3
    awesome-single-cell

    awesome-single-cell

    Community-curated list of software packages and data resources

    Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to address the statistical challenges of single cell RNA-seq. The package incorporates novel and established methods to provide a flexible framework to perform filtering, quality control, normalization, dimension reduction, clustering, differential expression and a wide-range of plotting. ...
    Downloads: 3 This Week
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  • 4
    .NET for Apache Spark

    .NET for Apache Spark

    A free, open-source, and cross-platform big data analytics framework

    .NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write...
    Downloads: 1 This Week
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  • 5
    Feather

    Feather

    Binary data frame storage for Python, R, and more

    ...It provides columnar serialization for data frames, making read and write operations faster than many text-based formats. The project was built to make sharing data across languages such as Python and R easier. Feather is powered by the Apache Arrow columnar memory specification, which helps it represent numeric, string, categorical, date, timestamp, boolean, and binary data efficiently. It also supports null and missing values across column types. Current development continues through Apache Arrow, with modern Python usage handled through pyarrow.feather.
    Downloads: 0 This Week
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  • 6
    JSMN

    JSMN

    Jsmn is a world fastest JSON parser/tokenizer

    JSMN (pronounced "jasmine") is a minimalistic JSON parser in C. It's tailored for resource-constrained environments, making it ideal for embedded systems where efficiency and low memory footprint are paramount.​
    Downloads: 0 This Week
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  • 7
    Savuka-VirtualBox

    Savuka-VirtualBox

    Virtual Box VDI of SliTaz Linux with Savuka installed and configured

    ...root name: root root password: root username: tux password: root Instructions: -Download and install 7zip (www.7-zip.org) -Extract files to HDD -Install included VirtualBox (not tested on other versions, but shouldn't matter) -Within VirtualBox make a new machine ----Machine/New --------Name: Savuka / Type: Linux / Version: Other Linux (32-bit) --------1024MB RAM -------- Use Existing virtual drive (point to extracted Savuka.vdi) ---- Machine/Settigns/Display: set video memory to 50 MB, enable 2D and 3D acceleration ---- Machine/Settings/Shared Folders: Create new machine folder. Point to any data directory, folder name: DATA, select Auto-mount. Note: "Folder name" must be 'DATA' in all caps to link on boot Thats it! More Info: www.osmanbilsel.net www.paulnobrega.net
    Downloads: 0 This Week
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