2 projects for "python text parser" with 2 filters applied:

  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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  • 1
    DataMelt

    DataMelt

    Computation and Visualization environment

    DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear...
    Downloads: 3 This Week
    Last Update:
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  • 2
    Feather

    Feather

    Binary data frame storage for Python, R, and more

    Feather is a fast, interoperable binary data frame storage format designed for efficient data exchange between analysis tools. 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. ...
    Downloads: 0 This Week
    Last Update:
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