Showing 4 open source projects for "numerical python"

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    Quantitative-Notebooks

    Quantitative-Notebooks

    Educational notebooks on quantitative finance, algorithmic trading

    Quantitative-Notebooks is a curated set of Jupyter notebooks focused on quantitative finance, algorithmic investing, and data-driven portfolio analysis. While each individual notebook is aimed at practical finance workflows, the overall repository helps practitioners and learners use Python, pandas, and numerical libraries to build, test, and evaluate financial strategies using historical market data. The notebooks typically showcase how to perform backtesting, factor analysis, risk assessment, and other quantitative workflows in a reproducible, exploratory format. Because quantitative analysis often requires visualization, statistics, and time series processing, these notebooks also serve as templates for real financial research and strategy prototyping. ...
    Downloads: 0 This Week
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  • 2
    DeepLearning

    DeepLearning

    Deep Learning (Flower Book) mathematical derivation

    " Deep Learning " is the only comprehensive book in the field of deep learning. The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including...
    Downloads: 3 This Week
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  • 3
    CasADi
    A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
    Downloads: 51 This Week
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  • 4
    Salstat2

    Salstat2

    statistical package designed for the end user, multiplatform

    Salstat2 is an statistical package written in python and designed for the end user It has a graphical user interface and also it is scriptable, It's multiplatform, It has a graphic system inherited from matplotlib, It allows you to use different libraries like numpy - for numerical calculations, it also lets you to interact with Microsoft Excel (R) by using a com client under windows(R) platform and finally you can create your own dialogs by using the interactive shell or the script panel.
    Downloads: 0 This Week
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