Search Results for "mathematical" - Page 4
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Showing 663 open source projects for "mathematical"
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PySINDy
A package for the sparse identification of nonlinear dynamical systems
PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. ... -
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Book5_Essentials-Probability-Statistics
The book 5 of statistics in simplicity
...The material connects probability theory directly to real analytical workflows, helping learners understand how statistics supports predictive modeling. Like the other books in the series, it blends mathematical explanation with Python-based experimentation. Overall, the project provides a practical statistical foundation for students advancing into AI and data science. -
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Easings.net
Easing Functions Cheat Sheet
Easings .net is a visualization and reference project dedicated to easing functions, which are widely used in animations and transitions to create natural motion. Instead of linear changes, easing functions help define how values accelerate or decelerate over time, resulting in smoother and more dynamic effects. The project provides a clear, interactive showcase of common easing equations such as quadratic, cubic, quartic, and elastic functions. It is a valuable resource for developers and... -
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All RL Algorithms from Scratch
Implementation of all RL algorithms in a simpler way
...Implemented topics include Q-learning, SARSA, Expected SARSA, Dyna-Q, REINFORCE, PPO, A2C, A3C, DDPG, SAC, TRPO, DQN, MADDPG, QMIX, HAC, MCTS, and PlaNet. The code prioritizes clarity, experimentation, and mathematical intuition over production speed. A companion cheat sheet gives learners a quick reference for formulas, pseudocode, and key concepts. -
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Swift Numerics
Advanced mathematical types and functions for Swift
Swift Numerics is a foundational library that extends the Swift standard library with essential numerical protocols, types, and functions needed for scientific and systems programming. It defines generic abstractions over real and complex numbers so algorithms can be written once and work across concrete floating-point types. The package includes RealModule utilities and a full Complex type with the expected arithmetic and transcendental functions, bridging a long-standing gap for numerics... -
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ThinkDSP
Digital Signal Processing in Python, by Allen B. Downey
Think DSP is an educational Python project that teaches digital signal processing through executable examples rather than starting with heavy mathematical formalism. It accompanies Allen B. Downey’s book and organizes most lessons as Jupyter notebooks. Readers work directly with waves, spectra, harmonics, filtering, convolution, and other signal-processing concepts. Early exercises show how to decompose sounds, modify frequency components, and synthesize new audio. The repository includes chapter notebooks, solution notebooks, sample sound files, book sources, and reusable Python code. ... -
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LaTeX Examples
Examples for the usage of LaTeX
...It acts as a playground for learning LaTeX syntax, macros, formatting tricks, and document structuring practices. Files include sample articles, reports, book chapters, presentations (using Beamer), tables, mathematical typesetting examples (equations, aligned systems, integrals, matrices), custom macros, and styling. The project is useful both for beginners who want to see working LaTeX samples and for more advanced users seeking snippets for specific formatting needs (e.g., customizing headers, floats, customizing theorem environments). Because examples are self-contained and well-commented, users can copy, adapt, or test them without needing a large TeX toolchain. -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
...The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric intuition, visualization, and step-by-step experimentation. It includes Jupyter notebooks and scripts that illustrate core machine learning topics such as regression, classification, optimization methods, and neural networks. These materials allow learners to see how algorithms behave during training and how different parameters affect model performance. -
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ESPectre
Motion detection system based on Wi-Fi spectre analysis (CSI)
ESPectre is an open-source motion detection system that transforms ordinary Wi-Fi signals into an ambient sensor capable of detecting movement without using cameras, microphones, or additional radio hardware, making it a privacy-preserving and cost-effective alternative for presence sensing and smart home automation. At its core, it analyzes Wi-Fi Channel State Information (CSI) — detailed measurements of how Wi-Fi waves change as they propagate — to mathematically detect disturbances caused... -
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Quick Look plugins
List of useful Quick Look plugins for developers
...The collection includes tools for Markdown, JSON, plain text, source code, archives, application bundles, installer packages, video, provisioning profiles, and various image formats. It also lists more specialized previewers for chemistry files, 3D-printing models, folders, and mathematical Markdown. Both free and commercial options are included, with installation information provided through Homebrew or manual installation where applicable. The repository functions as a maintained reference catalog rather than a single Quick Look extension. -
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
...The material emphasizes geometric interpretation and visual reasoning, which makes abstract linear algebra topics more accessible to beginners and self-learners. The repository is continuously updated and intended to accompany the broader Visualize-ML learning ecosystem. Overall, it serves as a visually driven mathematical foundation for students preparing for data science and machine learning work. -
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OpenBLAS
Optimized BLAS library based on GotoBLAS2 1.13 BSD version
OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. The Level 1 BLAS performs scalar, vector and vector-vector operations, the Level 2 BLAS performs matrix-vector operations, and the Level 3 BLAS performs matrix-matrix operations. Because the BLAS are efficient, portable, and widely available, they are commonly used in the... -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
...The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The GLM-Z1-32B-0414 line adds deeper mathematical, coding, and logical reasoning via extended reinforcement learning and pairwise ranking feedback, while GLM-Z1-Rumination-32B-0414 introduces a “rumination” mode that performs longer, tool-using deep research for complex, open-ended tasks. A lightweight GLM-Z1-9B-0414 brings many of these techniques to a smaller model, targeting strong reasoning under tight resource budgets. -
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pytudes
Python programs, usually short, of considerable difficulty
...The repository includes readable solutions, experiments, notebooks, and scripts that cover algorithms, puzzles, probability, search, language processing, simulation, and mathematical reasoning. It is useful for programmers who want to study elegant Python code while learning how experienced developers approach problem solving. Many examples emphasize clarity and compactness rather than framework-heavy engineering. pytudes is best understood as a learning library, a coding style reference, and a set of practical programming studies. -
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Book6_First-Course-in-Data-Science
From Addition, Subtraction, Multiplication, and Division to ML
Book6_First-Course-in-Data-Science is an open-source educational project that serves as part of the “Iris Book” series focused on teaching data science and machine learning concepts through a combination of mathematics, programming, and visualization. The repository contains draft chapters, supporting Python code, and visual materials designed to guide readers from basic mathematical operations toward practical machine learning understanding. The goal of the project is to make complex topics such as statistics, algorithms, and data analysis more accessible to learners by breaking concepts into clear explanations supported by code examples and diagrams. The material emphasizes a learning approach that combines theoretical knowledge with hands-on experimentation, often recommending interactive tools such as Jupyter notebooks to explore the ideas presented in the book. -
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Finance
150+ quantitative finance Python programs
Finance is a repository that compiles structured notes and educational material related to financial analysis, markets, and quantitative finance concepts. The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical... -
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Moondream
Tiny vision language model
...It serves as both a playground for the author’s artistic curiosity and a resource for other creative coders interested in generative art techniques. The repository may include shaders, canvas/WebGL code, visual demos, and utilities that demonstrate how mathematical functions or noise patterns can be harnessed for compelling visuals. -
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glChAoS.P
3D GPUs Strange Attractors and Hypercomplex Fractals explorer
glChAoS.P is a GPU-accelerated, real-time graphics project for visualizing complex mathematical fractals, attractors, and particle systems using OpenGL and GLSL. It’s an interactive sandbox for visual experimentation with chaotic systems, combining beautiful visuals with user control via keyboard and GUI. The software includes extensive customization of rendering parameters, camera movement, and output formats, including support for VR and 360-degree panoramic videos. -
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decimal.js
An arbitrary-precision Decimal type for JavaScript
...The library defines a Decimal constructor that accepts numbers, strings, or existing Decimal instances, enabling flexible usage across different input types. It supports a wide range of mathematical operations, including arithmetic, logarithmic, trigonometric, and exponential functions, making it significantly more comprehensive than simpler numeric libraries. -
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markstream-vue
A Vue 3 renderer specifically built for AI-powered streaming Markdown
...The framework focuses on eliminating jitter and reflow issues that commonly occur when rendering progressively generated text, ensuring a smooth and readable user experience even during rapid updates. It integrates advanced rendering support for complex content types such as code editors via Monaco, diagrams via Mermaid, and mathematical expressions via KaTeX, all optimized for incremental updates. The architecture is tailored for reactive front-end environments, leveraging Vue’s reactivity system to efficiently update only the necessary parts of the DOM. -
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Coconut
Training Large Language Model to Reason in a Continuous Latent Space
...It supports training across multiple reasoning paradigms—including standard Chain-of-Thought (CoT), no-thought, and hybrid configurations—using configurable training stages and latent representations. The repository is built with Hugging Face Transformers, PyTorch Distributed, and Weights & Biases (wandb) for logging, supporting large-scale experiments on mathematical and logical reasoning datasets such as GSM8K, ProntoQA, and ProsQA. -
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PowerPoint-ist
Web presentation editor replicating many PowerPoint features online
...PPTist is built with Vue 3 and TypeScript and focuses on providing a highly interactive slide editing environment with extensive customization and extension potential. PPTist supports a wide variety of slide elements such as text, images, shapes, charts, tables, audio, video, and mathematical formulas, enabling users to design rich and complex presentations. It also includes tools for slide organization, element alignment, animation, and theme management to streamline presentation design workflows. In addition to editing capabilities, it provides export options for presentation files and other formats, although compatibility with traditional presentation formats. -
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Machine learning algorithms
Minimal and clean examples of machine learning algorithms
...The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries. This approach allows learners to study the mathematical and algorithmic details behind widely used models in a transparent and readable way. The repository includes implementations of both supervised and unsupervised learning techniques, along with dimensionality reduction and clustering methods. Many of the algorithms are written in a simplified style that prioritizes clarity and educational value over production-level optimization. ... -
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PRIME
Scalable RL solution for advanced reasoning of language models
...PRIME provides training pipelines, datasets, and experimental infrastructure that allow researchers to train models with reinforcement learning tailored for reasoning improvement. The framework also includes data preprocessing utilities and example datasets such as mathematical reasoning tasks that are well suited for process-based reward signals. -
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Ling-V2
Ling-V2 is a MoE LLM provided and open-sourced by InclusionAI
...Trained on more than 20 trillion tokens of high-quality data and enhanced through multi-stage supervised fine-tuning and reinforcement learning, Ling-V2’s models demonstrate strong general reasoning, mathematical problem-solving, coding understanding, and knowledge-intensive task performance.
