Showing 4 open source projects for "nse options data"

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  • 1
    Interpolations.jl

    Interpolations.jl

    Fast, continuous interpolation of discrete datasets in Julia

    This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time.
    Downloads: 1 This Week
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  • 2
    Function Point Analysis

    Function Point Analysis

    Progressive Function Point Analysis Workbook in Excel

    Progressive Function Point Analysis Book Released: Print Copy: http://www.amazon.com/Progressive-Function-Point-Analysis-Estimation/dp/1502354160 EBook: http://www.amazon.com/dp/B00NH0MMAG Please support this project and its future releases ! Managers provide the architect/teams with project requirements. The architect/team returns detailed task list with estimated man hours per task making life easier for Project Managers with less guesstimates and proper business/technical process...
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    Downloads: 5 This Week
    Last Update:
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  • 3
    Active Learning

    Active Learning

    Framework and examples for active learning with machine learning model

    ...It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main experiment runner (run_experiment.py) supports a wide range of configurations, including batch sizes, dataset subsets, model selection, and data preprocessing options. It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. ...
    Downloads: 2 This Week
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  • 4

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A.
    Downloads: 0 This Week
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