13,787 skills found · Page 46 of 460
TezRomacH / Layer To Layer PytorchPyTorch implementation of L2L execution algorithm
cure-lab / Deep Active LearningAn implementation of the state-of-the-art Deep Active Learning algorithms
DavidEGrayson / Ruby EcdsaThis gem implements the Elliptic Curve Digital Signature Algorithm (ECDSA) almost entirely in pure Ruby.
hadipourh / KeeLoqC implementation of KeeLoq algorithm, equipped with a function to generate algebraic equations of KeeLoq over GF(2)
zhengqili / Unsupervised Learning Intrinsic ImagesImplementation of the intrinsic image decomposition algorithm described in "Learning Intrinsic Image Decomposition from Watching the World, Z. Li and N. Snavely, CVPR 2018"
TheAlgorithms / ClojureAll Algorithms implemented in Clojure
chynl / JumbleC/C++ implementations of data structures, algorithms, and common designs.
simplegeo / LibgeohashA pure C implementation of the Geohash algorithm.
Treeki / Libxbr StandaloneLibrary implementing the xBR pixel art scaling algorithm
neuromorphicsystems / Sgp4A Rust implementation of the SGP4 satellite propagation algorithm
m-hamza-mughal / Aerial Template MatchingThis project focuses on development of an algorithm for Template Matching on aerial images by implementing classical Computer Vision based techniques and deep-learning based techniques.
jaylmiller / Polyphonic TrackPolyphonic pitch tracking in real time using machine learning algorithms implemented in Python and an audio engine using Pure Data. Note tracking data is converted to MIDI and can be sent to DAWs, midi-capable hardware, etc.
ammarmahmood1999 / HeartHealthPredictionThe major reason for the death in worldwide is the heart disease in high and low developed countries. The data scientist uses distinctive machine learning techniques for modeling health diseases by using authentic dataset efficiently and accurately. The medical analysts are needy for the models or systems to predict the disease in patients before the strike. High cholesterol, unhealthy diet, harmful use of alcohol, high sugar levels, high blood pressure, and smoking are the main symptoms of chances of the heart attack in humans. Data Science is an advanced and enhanced method for the analysis and encapsulation of useful information. The attributes and variable in the dataset discover an unknown and future state of the model using prediction in machine learning. Chest pain, blood pressure, cholesterol, blood sugar, family history of heart disease, obesity, and physical inactivity are the chances that influence the possibility of heart diseases. This project emphasizes to evaluate different algorithms for the diagnosis of heart disease with better accuracies by using the patient’s data set because predictions and descriptions are fundamental objectives of machine learning. Each procedure has unique perspective for the modeling objectives. Algorithms have been implemented for the prediction of heart disease with our Heart patient data set
Sleen / FlexLayoutan implementation of Flexbox(Flexible Box) layout algorithm
patriceguyot / YinFast Python implementation of the Yin algorithm: a fundamental frequency estimator
Rustemsoft / Skater .NET ObfuscatorSkater .NET Obfuscator is an obfuscation tool for .NET code protection. It implements all known software protection techniques and obfuscation algorithms.
WuLC / KeywordExtractionImplementation of algorithm in keyword extraction,including TextRank,TF-IDF and the combination of both
TuringLang / AdvancedVI.jlImplementation of variational Bayes inference algorithms
jessesquires / Swift SortsA collection of sorting algorithms implemented in Swift
hlin117 / Mdlp DiscretizationAn implementation of the minimum description length principal expert binning algorithm by Usama Fayyad
