1,600 skills found · Page 7 of 54
BessieChen / Python For Financial Analysis And Algorithmic TradingIncluding packages that frequently used in quantitative finance field and how to implement classic financial model in Quantopian.
cinqmarsmedia / Trade Bots Algorithmic Trading GameA Technical Analysis Algorithmic Trading Game
ikizhvatov / PyscaToolbox for advanced differential power analysis of symmetric key cryptographic algorithm implementations
YuemingJin / MTRCNet CL[MedIA'20]Multi-task recurrent convolutional network with correlation loss for surgical video analysis, winner algorithm at MICCAI'19 Surgical Workflow and Skill Analysis Challenge
ElemarJR / Color Reduction With PcaA React application that reduces the color palette of images using Principal Component Analysis (PCA) and K-means clustering algorithms.
springer-math / Linear Programming Using MATLABThis book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.
JunjieYang97 / StocBiOExample code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"
plancherb1 / Parallel DDPCode supporting the WAFR paper "A Performance Analysis of Differential Dynamic Programming on a GPU," and the ICRA workshop follow on work deploying the algorithm onto robot hardware.
jmcilhargey / Chart Stock MarketA company tracking app that requests real time stock data via websocket connections and draws interactive graphs with d3.js and HTML5 canvas. Uses Twitter streaming data and algorithmic analysis to explore relationship between company performance and Twitter sentiment. HTML/CSS, Javascript, React, Node, Express, MongoDB, d3.js
adeeteya / Tennis Serve AnalysisThe Tennis Serve Analysis App is a mobile application designed to revolutionize the way tennis players analyze and improve their serves. Leveraging machine learning algorithms and computer vision techniques, the app provides users with personalized feedback of their serves.
simonaertssen / MIT 6.172 Performance Engineering Of Software Systems6.172 is an 18-unit class that provides a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming, and building scalable systems. The course programming language is C. See https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-172-performance-engineering-of-software-systems-fall-2018/
deadskull7 / Agricultural Price Prediction And Visualization On Android AppIn Agriculture Price Monitioring , I have used data provided by open government site data.gov.in, which updates prices of market daily . Working Interface Details: We have provided user choice to see current market prices based on two choices: market wise or commodity wise use increase assesibility options. Market wise: User have to provide State,District and Market name and then select market wise button. Then user will be shown the prices of all the commodities present in the market in graphical format, so that he can analyse the rates on one scale. This feature is mostly helpful for a regular buyer to decide the choice of commodity to buy. He is also given feature to download the data in a tabular format(csv) for accurate analysis. Commodity Wise: User have to provide State,District and Commodity name and then select Commodity wise button. Then user will be shown the prices of all the markets present in the region with the commodity in graphical format, so that he can analyse the cheapest commodity rate. This feature is mostly helpful for wholesale buyers. He is also given feature to download the data in a tabular format(csv) for accurate analysis. On the first activity user is also given forecasting choice. It can be used to forecast the wholesale prices of various commodities at some later year. Regression techniques on timeseries data is used to predict future prices. Select the type of item and click link for future predictions. There are 3 java files Forecasts, DisplayGraphs, DisplayGraphs2 ..... Please change the localhost "server_name" at time of testing as the server name changes each time a new server is made. Things Used: We have used pandas , numpy , scikit learn , seaborn and matplotlib libraries for the same . The dataset is thoroughly analysed using different function available in pandas in my .iPynb file . Not just in-built functions are used but also many user made functions are made to make the working smooth . Various graphs like pointplot , heat-map , barplot , kdeplot , distplot, pairplot , stripplot , jointplot, regplot , etc are made and also deployed on the android app as well . To integrate the android app and machine learning analysis outputs , we have used Flask to host our laptop as the server . We have a separate file for the Flask as server.py . Where all the the necessary stuff of clint request and server response have been dealt with . We have used npm package ngrok for tunneling purpose and hosting . A different .iPynb file is used for the time series predictions using regression algorithms and would send the csv file of prediction along with the graph to the andoid app when given a request .
rodrigoberriel / Ego Lane Analysis SystemEgo-Lane Analysis System (ELAS): Dataset and Algorithms (Image and Vision Computing, 2017)
tinylcy / RecommendationEngineSource code and dataset for paper "CBMR: An optimized MapReduce for item‐based collaborative filtering recommendation algorithm with empirical analysis"
titipata / Science Concierge:radio: a Python repository for content-based recommendation based on Latent semantic analysis (LSA) topic distance and Rocchio Algorithm, see the implementation interactively on
Atharvak19 / Big Data Medicare Fraud Detection4 different Big Datasets joined to get single table for final data analysis. Fraud Detection by taken consideration of different key features with applying different Machine Learning Algorithm to see which one performs better.
ratloop / MatchOutcomeAIA data-driven approach to predicting football match outcomes using advanced machine learning techniques. This project integrates various algorithms to forecast game results, providing insights for sports betting, team performance analysis, and sports enthusiasts.
renatovotto / NostradamusBacktesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.
mrtkp9993 / QuantitaveFinanceExamplesPyFinancial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir).
KrishnanSG / Holt WintersThe repository provides an in-depth analysis and forecast of a time series dataset as an example and summarizes the mathematical concepts required to have a deeper understanding of Holt-Winter's model. It also contains the implementation and analysis to time series anomaly detection using brutlag algorithm.
