1,600 skills found · Page 12 of 54
rohan-paul / Algorithm In JavaScriptImplementing all-time classic algorithmic problems in JS
arneish / CUDA PCA JacobiCUDA C implementation of Principal Component Analysis (PCA) through Singular Value Decomposition (SVD) using a highly parallelisable version of the Jacobi eigenvalue algorithm.
USACE-RMC / NumericsNumerics is a free and open-source library for .NET developed by USACE-RMC, providing a comprehensive set of methods and algorithms for numerical computations and statistical analysis.
dionyziz / Complexity ArticleA Gentle Introduction to Algorithm Complexity Analysis
linnarsson-lab / CytographAlgorithms for single-cell analysis
michaelsoltys / IAA CodeSolutions to programming problems in "An Introduction to the Analysis of Algorithms"
mick-liu / TagenalgoA genetic algorithm incorporated with technical analysis indicator to optimize parameters of a strategy.
usdaud / Algotradinglib.github.ioThis repository contains the source code and content for the website algotradinglib.com, focused on algorithmic trading and financial market analysis.
sunnymac / AdaAnalysis and Design of Algorithms(1010043316)
JustinGuese / Python Tradingbot FrameworkPython algorithmic trading bot framework for Kubernetes: backtesting, hyperparameter optimization, 150+ technical analysis indicators (RSI, MACD, Bollinger Bands, ADX), portfolio management, PostgreSQL integration, Helm deployment, CronJob scheduling. Minimal overhead, production-ready, Yahoo Finance data.
serkannpolatt / DATA SCIENCE FOR FINANCEThis repository features data science projects focused on financial data analysis and forecasting. The projects apply machine learning algorithms to analyze stock market data, predict trends, and optimize investment strategies.
wujr5 / Algorithm Analysis And Design算法分析与设计课程作业代码
xtekky / X Ss StubTikTok x-ss-stub algorithm analysis | encryption algorithm
omidvarnia / Dynamic Brain Connectivity AnalysisThis repository covers our developed algorithms and techniques for dynamic brain connectivity analysis.
zoisboukouvalas / PyivaImplementation of the independent vector analysis (IVA) algorithm using a multivariate Laplace prior
corticph / Error AlignText-to-text alignment algorithm for speech recognition error analysis.
zahta / Graph Machine LearningCourse: Graph Machine Learning focuses on the application of machine learning algorithms on graph-structured data. Some of the key topics that are covered in the course include graph representation learning and graph neural networks, algorithms for the world wide web, reasoning over knowledge graphs, and social network analysis.
timothyjgraham / AlgorithmicBiasXCode and instructions for technical report: "A computational analysis of potential algorithmic bias on platform X during the 2024 US election" (Graham & Andrejevic, 2024)
xjtushilei / ChineseStarsRelationship中国明星数据爬取。你甚至可以拿到互联网上所有的人之间的关系，接下来你可以自己发挥！基于这些数据，你可以完成更多有趣的事情。比如说社交网络分析，关系网络可视化，算法研究，和其他有意思的事情。Chinese star data crawling. You can even get all the people on the internet! Based on these data, you can do more interesting things. For example, social network analysis, relational network visualization, algorithm research, and other interesting things.
Ilyushin / EconomicIntelligenceThe project focused on the use of public data to assess the economic situation in the country based on the state of the stock market and national means of payment, in particular - of the national currency. As sources are used: Open data Ministry of Finance of the Russian Federation These Moscow Exchange Google Finance Data Technologies used: Backend: Databases (relational) - Microsoft SQL Server 2014 Databases (multivariate) models DataMining, OLAP-cube - Microsoft Analysis Services 12.0 Веб-сервер - Windows Server 2012 / Internet Information Services Самописный ASP.NET HTTP Restful интерфейс для взаимодействия с Frontend ETL (загрузка и пре-процессинг данных, управление обновлением данных) SQL Server Integration Services 2014 (разработка в Visual Studio 2013, SSDT) Frontend: AngularJS ChartJS Twitter Bootstrap These were chosen so that the detail (granularity) in the set is not less than 1 day. The result has been created and filled with data analytic repository (Kimball model, topology - star), which was used to build a multi-dimensional databases and OLAP-based cubes on it, as well as models of analysis of data on two main algorithms: Microsoft Time Series, Microsoft Neural Network . To ensure interoperability frontend and backend server for backend-server was set up HTTP-Restful interface JSON-issuing documents in the form of finished sets. The project includes two main areas: Intelligent visualization of open data Analysis of open data and the construction of forecasts based on them Intelligent visualization involves the use of MDX-queries to the OLAP-cube, followed by depression (drilldown) in the data, the system allows the user to quickly find the "weak points" of the economy, as part of the data collected. To predict the time a standard mix of algorithms ARTXP / ARIMA, without the use of queries involving cross-prediction (but it is possible to enroll in the system correct data). These algorithms have been tested primarily on foreign exchange rates (US dollar) and the assets of banks included in the special list of Ministry of Finance. In addition, for assets shows the different customization options algorithms - a long-term, short-term and medium-term (balanced) plan. Assessing the impact of oil prices and foreign currency exchange rate for the total market capitalization was conducted on a sample of the data collected: companies with a total market capitalization of 100 to 500 million rubles, present in the market during 2013-2015 Analytical server builds the neural network receiving the input exchange rates, companies, the weighted average share price, total capitalization of the company and the price of oil to requests received models give the opportunity to evaluate the growth rate of \ fall (if at all) the company's capitalization at historical exchange rates and / or the cost of oil. Built a system can expand to include new indicators, which will significantly increase the accuracy of forecasting.
