<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title>Bing: SciPy Library Logo</title><link>http://www.bing.com:80/search?q=SciPy+Library+Logo</link><description>Search results</description><image><url>http://www.bing.com:80/s/a/rsslogo.gif</url><title>SciPy Library Logo</title><link>http://www.bing.com:80/search?q=SciPy+Library+Logo</link></image><copyright>Copyright © 2026 Microsoft. All rights reserved. These XML results may not be used, reproduced or transmitted in any manner or for any purpose other than rendering Bing results within an RSS aggregator for your personal, non-commercial use. Any other use of these results requires express written permission from Microsoft Corporation. By accessing this web page or using these results in any manner whatsoever, you agree to be bound by the foregoing restrictions.</copyright><item><title>SciPy</title><link>https://scipy.org/</link><description>SciPy provides algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems.</description><pubDate>Thu, 26 Mar 2026 07:20:00 GMT</pubDate></item><item><title>SciPy - Installation</title><link>https://scipy.org/install/</link><description>Here is a step-by-step guide to setting up a project to use SciPy, with uv, a Python package manager. Install uv following, the instructions in the uv documentation.</description><pubDate>Fri, 10 Apr 2026 13:36:00 GMT</pubDate></item><item><title>SciPy documentation — SciPy v1.17.0 Manual</title><link>https://docs.scipy.org/doc/scipy/</link><description>The reference guide contains a detailed description of the SciPy API. The reference describes how the methods work and which parameters can be used. It assumes that you have an understanding of the key concepts.</description><pubDate>Sun, 12 Apr 2026 00:19:00 GMT</pubDate></item><item><title>SciPy User Guide — SciPy v1.17.0 Manual</title><link>https://docs.scipy.org/doc/scipy/tutorial/index.html</link><description>SciPy User Guide # SciPy is a collection of mathematical algorithms and convenience functions built on NumPy . It adds significant power to Python by providing the user with high-level commands and classes for manipulating and visualizing data. Subpackages and User Guides # SciPy is organized into subpackages covering different scientific computing domains. These are summarized in the ...</description><pubDate>Fri, 10 Apr 2026 13:21:00 GMT</pubDate></item><item><title>SciPy</title><link>https://scipy.org/ja/</link><description>Scipy は、FortranやC, および C++ のような低レベル言語で書かれた高度に最適化された実装を利用し、高速な計算を実現します。 コンパイルされたコードのスピードを保ちつつ、Python の柔軟性をお楽しみください。</description><pubDate>Fri, 10 Apr 2026 12:17:00 GMT</pubDate></item><item><title>Optimization (scipy.optimize) — SciPy v1.17.0 Manual</title><link>https://docs.scipy.org/doc/scipy/tutorial/optimize.html</link><description>The minimum value of this function is 0 which is achieved when x i = 1. Note that the Rosenbrock function and its derivatives are included in scipy.optimize. The implementations shown in the following sections provide examples of how to define an objective function as well as its jacobian and hessian functions. Objective functions in scipy.optimize expect a numpy array as their first parameter ...</description><pubDate>Sat, 11 Apr 2026 05:28:00 GMT</pubDate></item><item><title>Numpy and Scipy Documentation</title><link>https://docs.scipy.org/doc/</link><description>Numpy and Scipy Documentation ¶ Welcome! This is the documentation for Numpy and Scipy. For contributors: Numpy developer guide Scipy developer guide Latest releases: Complete Numpy Manual [HTML+zip] Numpy Reference Guide [PDF] Numpy User Guide [PDF] F2Py Guide SciPy Documentation [HTML+zip] Others:</description><pubDate>Sun, 12 Apr 2026 03:18:00 GMT</pubDate></item><item><title>SciPy API — SciPy v1.17.0 Manual</title><link>https://docs.scipy.org/doc/scipy/reference/</link><description>SciPy API # Importing from SciPy # In Python, the distinction between what is the public API of a library and what are private implementation details is not always clear. Unlike in other languages like Java, it is possible in Python to access “private” functions or objects. Occasionally this may be convenient, but be aware that if you do so your code may break without warning in future ...</description><pubDate>Wed, 08 Apr 2026 08:09:00 GMT</pubDate></item><item><title>SciPy - インストール</title><link>https://scipy.org/ja/install/</link><description>SciPyの推奨されるインストール方法は、あなたの好みのワークフローによって異なります。 一般的なワークフローは、大きく以下のカテゴリに分類できます。 一般的なワークフローは大まかに下記のカテゴリに分類できます。 プロジェクトベース (例: uv, pixi) (新規ユーザーに推奨) 環境ベース ...</description><pubDate>Wed, 08 Apr 2026 15:11:00 GMT</pubDate></item><item><title>Statistical functions (scipy.stats) — SciPy v1.17.0 Manual</title><link>https://docs.scipy.org/doc/scipy/reference/stats.html</link><description>Statistical functions (scipy.stats) # This module contains a large number of probability distributions, summary and frequency statistics, correlation functions and statistical tests, masked statistics, kernel density estimation, quasi-Monte Carlo functionality, and more. Statistics is a very large area, and there are topics that are out of scope for SciPy and are covered by other packages ...</description><pubDate>Fri, 10 Apr 2026 22:25:00 GMT</pubDate></item></channel></rss>