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3 Repos

Awesome GitHub RepositoriesNumerical Computing References

Instructional guides and references for performing high-performance mathematical operations on multi-dimensional arrays.

Distinct from NumPy-Compatible Frameworks: The candidates focus on specific integration layers or distributed workflows, whereas this is a general educational reference for NumPy.

Explore 3 awesome GitHub repositories matching scientific & mathematical computing · Numerical Computing References. Refine with filters or upvote what's useful.

Awesome Numerical Computing References GitHub Repositories

Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
  • iamseancheney/python_for_data_analysis_2nd_chinese_versionAvatar von iamseancheney

    iamseancheney/python_for_data_analysis_2nd_chinese_version

    8,937Auf GitHub ansehen↗

    This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p

    Provides a comprehensive reference for high-performance vectorized operations and linear algebra using NumPy.

    matplotlibnumpypandas
    Auf GitHub ansehen↗8,937
  • lijin-thu/notes-pythonAvatar von lijin-THU

    lijin-THU/notes-python

    7,132Auf GitHub ansehen↗

    This project is a collection of educational notes and tutorials focused on Python programming, scientific computing, and data analysis. It serves as a reference for learning language basics, advanced techniques, and object-oriented design. The materials include implementation guides for building linear, logistic, and convolutional neural networks using symbolic graph frameworks. It also provides instruction on manipulating and visualizing structured data frames and performing complex mathematical operations through numerical libraries. The repository includes a system for converting interact

    Provides an instructional guide for performing high-performance mathematical operations on multi-dimensional arrays.

    Jupyter Notebookanacondamatplotlibnumpy
    Auf GitHub ansehen↗7,132
  • jwarmenhoven/coursera-machine-learningAvatar von JWarmenhoven

    JWarmenhoven/Coursera-Machine-Learning

    859Auf GitHub ansehen↗

    This repository serves as an educational collection of Python implementations for fundamental machine learning algorithms and statistical models. It provides a structured environment for learning core concepts through interactive computational documents that combine live code, narrative text, and data visualizations. The codebase focuses on predictive modeling development, offering instructional examples for building and evaluating regression, classification, and neural network models. It utilizes standardized data science library interfaces to demonstrate how to implement and execute these a

    Provides instructional references for performing high-performance mathematical operations on multi-dimensional arrays.

    Jupyter Notebookandrew-ngcoursera-machine-learningpredictive-modeling
    Auf GitHub ansehen↗859
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