Search Results for "tiny-core-plus" - Page 2
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Showing 268 open source projects for "tiny-core-plus"
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ccgsl
Use Gnu Scientific Library as if it were writtem in C++.
The ccgsl provides simple C++ wrappers for the GNU Scientific Library. It uses Java-like shared-pointer classes in place of structs to avoid direct memory allocation/freeing and to work better with the STL. It lets you construct functions for optimisation, root-finding and the like from C++ member functions, making it easier to integrate with existing C++ code. It also provides C++ exceptions. -
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ringBufU
Ring-Buffer library in C, includes support of multithreading
A Ring-Buffer instance could be used with element types - char - long - long long - void* . Focus is on a hardened SW structure with buffer-instance-pointer check (not very fast but more secure). Some features are globally choosable on compile-time (e.g. switch multithread support off completely to have faster access). Note: User Interface is for Test and Tutor Code only. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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Thrust
The C++ parallel algorithms library
Thrust is the C++ parallel algorithms library which inspired the introduction of parallel algorithms to the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. It builds on top of established parallel programming frameworks (such as CUDA, TBB, and OpenMP). It also provides a number of general-purpose facilities similar to those found in the C++ Standard Library. The NVIDIA C++... -
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Clipper
Polygon and line clipping and offsetting library (C++, C#, Delphi)
This library is now obsolete and no longer being maintained. It has been superceded by my Clipper2 library - https://github.com/AngusJohnson/Clipper2. -
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D-List
An extensive list subsystem, written in C
D-List is an extensive, production quality, and robust list management subsystem written in C that can be used as a shared library or compiled directly into your project. D-List provides access to 3 classes of lists, and allows extensive manipulation and customization of these lists. D-List lists can also be easily incorporated as primitives into larger treed, or nested data management systems. D-List implements a comprehensive set of linked list primitives that provides multiple forms of... -
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CountBitsSet
minimal benchmark code for Counting Set Bits (ones) in an Integer
I was curious how much better the Algorithms, pointed out by BitTwiddling Hacks, perform than a simple Lookup Table approach... Now I think, perhaps my little investigation is interesting for others too... PS: the parallel counting Algo is about 35% faster on average on my computers than a simple LUT based solution. Also this shows nicely how different a human brain compatible solution is to a binary machine optimal solution :-) In the meantime I added other Algorithms beside... -
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go-algorithms
Algorithms and data structures for golang
go-algorithms is an open-source educational repository that provides implementations of common algorithms and data structures written in the Go programming language. The project is designed primarily as a learning resource to help developers understand how fundamental computer science concepts can be implemented idiomatically in Go. It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and... -
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JS-Sorting-Algorithm
A GitBook online book on sorting algorithms
JS-Sorting-Algorithm is an educational repository and GitBook-style resource about classic sorting algorithms. It explains sorting as a core topic in data structures and algorithms, with attention to internal sorting, external sorting, time complexity, memory usage, and stability. The guide covers ten major sorting methods, including bubble sort, selection sort, insertion sort, shell sort, merge sort, quicksort, heap sort, counting sort, bucket sort, and radix sort. It compares algorithms by complexity classes such as quadratic time, linearithmic time, and linear time. ... -
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Machine Learning Cheat Sheet
Classical equations and diagrams in machine learning
This repository is a visually rich and well-organized “cheat sheet” summarizing core machine learning concepts, algorithms, formulas, and best practices. It includes summaries of supervised and unsupervised learning methods, model evaluation metrics (accuracy, precision, recall, ROC/AUC), overfitting/underfitting, regularization (L1/L2), cross-validation, feature engineering techniques, and perhaps tips for hyperparameter tuning. -
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TA-Lib.git: Technical Analysis Library
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project. -
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libPGF
libPGF is an implementation of the Progressive Graphics File (PGF)
The Progressive Graphics File (PGF) is an efficient image file format, that is based on a fast, discrete wavelet transform with progressive coding features. PGF can be used for lossless and lossy compression. It's most suitable for natural images. PGF can be used as a very efficient and fast replacement of JPEG 2000. -
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Base62 Encode/Decode Utility
A tool for encoding/decoding to base62
the package chewingum contains two main programs: - base62 - chew They have been implemented in perl. Base62 has been coded in c++ too. chew has been written to shorten long decimal integer numbers into base62 strings. It's not a mere base conversion, because it doesn't use arithmetic inside its logic. In this way it can convert very long numbers into strings quickly, without overflows. For example if I want to share an id using an url, this will make the url shorter. the... -
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ExRandom
Sampling exactly from the normal and exponential distributions
ExRandom is a small header-only C++11 library for exact sampling from the normal, exponential, and discrete normal distributions (provided that the underlying generator is perfect). This library provides an implementation of the algorithms described in C. F. F. Karney, Sampling exactly from the normal distribution, ACM Trans. Math. Software 42(1), 3:1-14 (Jan. 2016), https://doi.org/10.1145/2710016, https://arxiv.org/abs/1303.6257. -
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Fun4Me
A package for functional annotation for metagenomes
This package includes a few programs for rapid functional annotation for metagenomic sequences, including, 1) Gene prediction by FragGeneScan; 2) Similarity search by RAPSearch2; 3) Functional annotation in GO (Gene Ontology) and EC (Enzyme Commission) based on similarity search results; 4) From EC to metabolic pathway reconstruction by MinPath. Inputs: Just sequencing reads (or assemblies) Outputs: Protein-coding genes (or gene fragments); similarity search; functional annotations... -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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AhoCorasickDoubleArrayTrie
An extremely fast implementation of Aho Corasick algorithm
AhoCorasickDoubleArrayTrie is a Java implementation of the Aho–Corasick multi-pattern matching algorithm that is optimized using a Double-Array Trie data structure. It is designed for fast keyword scanning across large texts, where you want to search for many patterns simultaneously and efficiently. The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. By using a double-array trie representation, the project emphasizes performance and memory efficiency compared to simpler pointer-heavy trie structures, which can matter a lot for large dictionaries or latency-sensitive services. ... -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry. -
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TRSL is a C++ library that implements several (statistical) sampling schemes behind an (STL-like) iterator interface. The library may be used e.g. in particle filtering. It is distributed under the Boost SL (BSL is a free-software license).
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mssolutions
Makes magic squares.
These programs make magic squares and rectangles using "Constraint-Based Local Search". (For non-square rectangles, input the order as two numbers.) There are 3 similar programs: CompleteSquare, CompleteSquareSteps, and MagicSquares. Given an input square with some cell values between 1 and NxN specified, (and other cell values 0), CompleteSquare attempts to complete a magic square by placing the remaining values. The square type can be input as semimagic, magic, or... -
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PythonRobotics
Python sample codes and textbook for robotics algorithms
...It covers practical topics such as localization, mapping, path planning, path tracking, control, SLAM, and autonomous navigation. The project is written to make each algorithm’s core idea easy to understand, rather than hiding the logic behind large frameworks. It keeps dependencies minimal so learners can focus on the math, implementation, and behavior of each robotics method. Visual examples and simulations help users see how algorithms move, estimate, plan, and react. PythonRobotics is especially useful for students, researchers, and engineers who want a hands-on reference for robotics fundamentals in Python. -
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Kalibr Allan
IMU Allan standard deviation charts
kalibr_allan is a utility repository that provides scripts and tools for calculating IMU noise parameters for use in Kalibr and other IMU filtering systems. While manufacturers typically provide “white noise” values in IMU datasheets, the bias instability and random walk parameters must be determined experimentally. This project enables users to compute those values using Allan variance analysis from recorded IMU data. The workflow involves recording IMU measurements with the device... -
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C++ BigInt class
C++ BigInt class enables to work with arbitrary precision integers
C++ BigInt class that enables the user to work with arbitrary precision integers. Latest Version: 10.3 (2019-03-06) -
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TSP Solver and Generator
Generate and solve Travelling Salesman Problem tasks
TSPSG is intended to generate and solve Travelling Salesman Problem (TSP) tasks. It uses Branch and Bound method for solving. An input is a number of cities and a matrix of city-to-city travel prices. The matrix can be populated with random values in a given range (useful for generating tasks). The result is an optimal route, its price, step-by-step matrices of solving and solving graph. The task can be saved in internal binary format and opened later. The result can be printed or saved as... -
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NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
