Search Results for "python math" - Page 2
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Showing 123 open source projects for "python math"
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is... -
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Qwen
The official repo of Qwen chat & pretrained large language model
Qwen is a series of large language models developed by Alibaba Cloud, consisting of various pretrained versions like Qwen-1.8B, Qwen-7B, Qwen-14B, and Qwen-72B. These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. Qwen's capabilities include text generation, comprehension, and conversation, making it a... -
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Mathematics Dataset
This dataset code generates mathematical question and answer pairs
The Mathematics Dataset, developed by Google DeepMind, is a synthetic dataset designed to evaluate and train machine learning models on mathematical reasoning and symbolic manipulation. It generates question-and-answer pairs across a wide range of mathematical topics typically found in school-level curricula, testing a model’s ability to reason about algebra, arithmetic, calculus, probability, and more. Each question is programmatically generated with structured templates to ensure clear... -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
micrograd is a tiny, educational automatic differentiation engine focused on scalar values, built to show how backpropagation works end to end with minimal code. It constructs a dynamic computation graph as you perform math operations and then computes gradients by walking that graph backward, making it an approachable “from scratch” autograd reference. On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple... -
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llm.c
LLM training in simple, raw C/CUDA
llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and... -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The... -
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Little Book of Linear Algebra
A concise, beginner-friendly introduction to the core ideas of linear
...The material is organized into chapters covering vectors, matrices, linear systems, vector spaces, eigenvalues/eigenvectors, and other central topics, each with worked examples and explanations. There is also a companion “LAB” section for hands-on exploration (e.g. using Python/NumPy) to help cement the connections between algebraic formulas and computational behavior. The exposition aims to sit between a pop-math summary and a heavy textbook: definitions and key theorems are stated cleanly, while proofs are sometimes omitted or sketched to keep the flow digestible. Because of its brevity and clarity, it's especially useful as a first pass for learners who want a solid map of the subject before diving into full textbooks. -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. 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... -
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LeetCode Book
Comprehensive study guide for coding interviews
LeetCode-Book is a comprehensive study guide for coding interviews that consolidates algorithm patterns, data-structure templates, and worked LeetCode solutions. It organizes problems by topic—arrays, linked lists, stacks/queues, trees/graphs, dynamic programming, greedy, backtracking, and math—so you can study systematically. Explanations are concise but intentional, highlighting why a pattern fits, how to reason about boundary cases, and the time/space trade-offs. Many entries include... -
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Slot math toolkit
Python toolkit for slot machine RTP verification and variance analysis
Slot Math Toolkit is an open-source Python library for slot machine math: RTP verification via Monte Carlo simulation, Bonus Buy ROI analysis, variance scoring (1-5 scale), and single-session simulation. Sample data for Sugar Rush series (Original, 1000, Super Scatter), Sweet Bonanza, Gates of Olympus, Mega Joker, Ugga Bugga. For the full Sugar Rush Super Scatter methodology including paytable breakdowns and Super Scatter multiplier ranges (x100/x500/x5000/x50000), see the detailed mechanics breakdown at https://sugarrush-super-scatter.com/ Core features: - RTP Calculator with 95% confidence intervals - Bonus Buy ROI Analyzer (x100 standard, x500 super) - Variance Scorer via coefficient of variation - Session Simulator with bankroll, bet size, stop-loss Install: pip install slot-math-toolkit CLI: slot-math rtp --slot sugar_rush_super_scatter --spins 100000 41 tests, 94% coverage. ... -
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Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
Open Gauss is an enterprise-grade open-source relational database management system designed to handle large-scale data processing with high performance, reliability, and security. It is based on the PostgreSQL ecosystem but significantly extends its capabilities through architectural optimizations, AI-driven features, and enterprise-level enhancements. The database organizes data using the relational model, storing structured information in tables composed of rows and columns while... -
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Skywork-R1V4
Skywork-R1V is an advanced multimodal AI model series
Skywork-R1V is an open-source multimodal reasoning model designed to extend the capabilities of large language models into vision-language tasks that require complex logical reasoning. The project introduces a model architecture that transfers the reasoning abilities of advanced text-based models into visual domains so the system can interpret images and perform multi-step reasoning about them. Instead of retraining both language and vision models from scratch, the framework uses a... -
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Super comprehensive deep learning notes
Super Comprehensive Deep Learning Notes
Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to... -
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PLplot
Cross-platform, scientific graphics plotting library
PLplot is a cross-platform, scientific graphics plotting library that supports math symbols and human languages (via UTF-8 user input strings); plot capabilities for multiple non-interactive plot file formats and in multiple interactive environments; and bindings for multiple computer languages. -
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Napkin
An Infinitely Large Napkin
Napkin (also titled “An Infinitely Large Napkin”) is a lightweight, semi-formal introduction to higher mathematics, aimed at giving readers a bird’s-eye view over various mathematical fields. It is not a polished textbook full of full proofs; rather it offers clean definitions, theorem statements, intuitive motivations, and informal sketches of why things work, with the goal of building conceptual understanding. The coverage spans undergraduate and early graduate topics, designed to show how... -
17
Minsky
System dynamics program with additional features for economics
Minsky brings system dynamics and monetary modelling to economics. Models are defined using flowcharts on a drawing canvas (as are Matlab's Simulink, Vensim, Stella, etc). Minsky's unique feature is the "Godley Table", which uses double entry bookkeeping to generate stock-flow consistent models of financial flows. Minsky is good for demonstrating mathematics too, with the most "math-like" interface in system dynamics. Sign up to Minsky's Patreon page (for as little as $1 a month) at... -
18
Abscom
A C11 library of reusable data structures and platform utilities.
Abscom bundles low-level building blocks — dynamic arrays, growable strings, hash functions, an open-addressing hash map, timing helpers, and simple file I/O — under a single umbrella header. On top of that it ships a Python-inspired dynamic runtime that brings var values, lists, dictionaries, sets, JSON, random utilities, and a light object system to plain C, plus a scientific layer with matrices, statistics, general math (scalar utilities, number theory, geometry, complex numbers), CSV, path helpers, and basic threading. A data science layer adds NumPy-style reshaping and generators, Pandas-style numeric CSV, functional utils, and SciKit-Learn-style preprocessing (one-hot encoding, train/test split). ... -
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The Grand Complete Data Science Guide
Data Science Guide With Videos And Materials
The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. The repository bundles tutorials, lecture notes, project outlines, course materials, and references across topics like Python, statistics, ML algorithms, deep learning, NLP, data preprocessing, model evaluation, and real-world problem solving. ... -
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PyNotes
An advanced Emacs-like text editor and IDE made in Python.
PyNotes is an advanced Emacs-like text editor and IDE made in Python, but much simpler for new users. -
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Cobalt is a lightweight, experimental, fully object-oriented programming language built using Python. It is designed for learning programming concepts, language design, and rapid prototyping. Cobalt provides support for all major OOP features, including classes, objects, inheritance, polymorphism, abstraction, encapsulation, constructors, and reusable modular code design. The language uses a custom interpreter that performs lexical analysis, parsing, and runtime execution.
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DeepSeek Math
Pushing the Limits of Mathematical Reasoning in Open Language Models
DeepSeek-Math is DeepSeek’s specialized model (or dataset + evaluation) focusing on mathematical reasoning, symbolic manipulation, proof steps, and advanced quantitative problem solving. The repository is likely to include fine-tuning routines or task datasets (e.g. MATH, GSM8K, ARB), demonstration notebooks, prompt templates, and evaluation results on math benchmarks. The goal is to push DeepSeek’s performance in domains that require rigorous symbolic steps, calculus, linear algebra, number... -
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3D Box rotation
Simple example of draw and rotate 3D box
...Rotation speed regulated in simple Loop with 10 ms sleep. Use Java version 8 (OpenJDK 8, OracleJDK 8, OracleJRE 8, ..). Higher versions have an anti-aliasing error in the BufferedImage ( Windows 10 ). Python version with tkinter and math imports. Including calculated faces, moving lights and shadows only with CPU. -
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Advanced Trigonometry Calculator
Open-source C/C++ math engine for advanced scientific computing
Advanced Trigonometry Calculator (ATC) is an open-source mathematical computing engine written mainly in C/C++. Created in 2011 and maintained by Renato Alexandre dos Santos Freitas, ATC is designed as a practical Windows desktop application for advanced calculations, automation, and technical problem solving. ATC supports equation solving, polynomial tools, complex numbers, matrix calculations, statistics, physics, geometry, unit conversions, DSP/FFT operations, and scripting. It can... -
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mkdocs-void
Void is a new design language for MkDocs themes: a drop-in theme (name
Void is a custom MkDocs theme that blends the translucent, layered aesthetics of Glass design system with the minimal, industrial clarity of NothingOS. It combines pure black canvas, glass morphism panels, dot-matrix typography, and Nothing Red accents into a cohesive documentation experience.
