Showing 3 open source projects for "dependency"

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    Python for Data Analysis

    Python for Data Analysis

    Materials and IPython notebooks for "Python for Data Analysis"

    ...Its chapters cover Python basics, NumPy, pandas, data loading, cleaning, wrangling, visualization, time series, modeling libraries, and full analysis examples. The project includes setup options using uv or Conda, with dependency files to reproduce the working environment. It is best suited for learners, analysts, and developers who want hands-on practice with the modern Python data stack.
    Downloads: 4 This Week
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  • 2
    q pipeline manager

    q pipeline manager

    q: integrated platform for pipeline configuration and management

    ...Data processing pipelines require high-level organization and parallelization of work to optimize resource utilization and decrease the time to results. q (from queue) allows complex job sequences to be efficiently assembled and managed, including dependency tracking, parallelization, and pipeline-level monitoring, error recovery, and data protection. Pipelines are constructed from modular script files, with job definitions and results stored in easily retrieved job files. A web interface facilitates job submission and monitoring, with the complete pipeline exportable for full transparency.
    Downloads: 0 This Week
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  • 3
    JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
    Downloads: 0 This Week
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