1,602 skills found · Page 33 of 54
CodeByPinar / Spotify Trends 2023 AnalysisExploring Spotify's latest trends, top songs, genres, and artists using Python, Pandas, NumPy, Matplotlib, CNNs for image-based analysis, and advanced algorithms for music recommendation. Dive into the world of music data and discover what's trending on Spotify! 🎵📊
charalambos / P2C ClusteringClustering module in IEEE PAMI 2013: A Framework for Automatic Modeling from Point Cloud Data. A robust unsupervised clustering algorithm P2C, based on a hierarchical statistical analysis of the geometric properties of the data.
pixelwhiz / Tasty Schwab Trader BEMulti-strategy algorithmic trading platform designed for institutional-grade automated execution across futures, equities, and options markets. Built with Python and Flask, this system provides real-time market analysis, multi-broker integration, and comprehensive risk management capabilities.
abhiupes01 / Pressure Drop PredictionThe repository is the implementation of a research paper concluding the performance analysis of machine learning algorithm on complex non-Newtonian fluids.
surgesg / PyOraclePyOracle is a project using Python to analyze aspects of musical structure. Audio Oracle, an algorithm based on the Factor Oracle string matching algorithm, is used to detect introductions and repetitions of musical materials. Through this analysis, aspects of musical structure can be understood, and new versions of the analyzed work can be created.
kuberkaul / SentimentAnalysis MovieReviewsThe projects takes a number of movie reviews from http://www.cs.cornell.edu/people/pabo/movie-review-data/ (polarity dataset v2.0 and an independent dataset) and using SVM, Naive Bayes, KNN algorithms analysis the sentiment behind that review to being either positive or negative. The prediction is then compared to the actual sentiment behind the review and higher precision is targeted between all three algorithm. The research is then followed by a technical paper.
Lweb / KPLEXThis project includes the source code and the complete experimental results of the paper "A Fast Algorithm to Compute Maximum k-Plexes in Social Network Analysis".
hoangsonww / Graph Data Structure🔍 This repository explores the graph data structure, focusing on its application in analyzing large texts and developing the Word Graph Game. It includes algorithms for text analysis, graph construction, and game logic, offering a comprehensive toolkit for educational and development purposes.
hoangsonww / Standard Deviation Calculator📊 This repository contains a Standard Deviation Calculator implemented in C++. It provides an efficient algorithm for calculating the statistical standard deviation of a dataset, making it a valuable tool for students, researchers, and analysts seeking a reliable method for data analysis.
MasihMoafi / Financial Market AnalysisFinancial market analysis using time-series models, clustering algorithms, Transformers, and reinforcement learning for trading strategies.
ImMamey / Numeric Calc TicxinspireII CodeAutomated codes from Numerical analysis / numerical methods / Numerical calculus algorithms for TI-Nspire cx cas II calculators.
tylergrreid / L5 SBAS MOPS Ephemeris Fitting AlgorithmThis matlab code fits the L5 SBAS MOPS ephemeris message parameters to precision orbit data. It also performs fit error analysis and evaluates the message performance. Specificially, this looks at the corner cases that can cause problems with the fitting algorithm convergence. This implements the algorithms outlined in Appendix B of my PhD thesis undertaken in the GPS Research Lab in the Department of Aeronautics and Astronautics at Stanford University, entitled, "Orbital Diversity for Global Navigation Satellite Systems"
vimal0156 / QuantumTrade NexusAdvanced Trading Intelligence Platform - Comprehensive financial analysis toolkit with 15+ technical indicators, algorithmic strategies, and real-time market intelligence
Lipapaldl / HZAU ADA华中农业大学-算法设计与分析课程期末Algorithm Design and Analysis
GourangaDasSamrat / Online Judge SolutionsA comprehensive collection of Data Structures and Algorithms solutions from competitive programming platforms, featuring automated synchronization and AI-powered complexity analysis.
serena049 / Implementation Of The Frank Wolfe AlgorithmThe purpose this project is to implement the Frank-Wolfe Algorithm for transportation network analysis. The next section summarizes the key steps involved in the Python coding process, followed by two traffic assignment applications. The report is concluded with a discussion of findings and future plans.
revaturelabs / BiforceBiforce is a project conducted by Revature to improve its business decisions via re-examination of existing metrics and investigation into new metrics that will increase value of company assets. The goal is to leverage all relevant technologies to automate the process of data analysis within the business intelligence life cycle conducted on different departments within the company. The objective is to implement efficient algorithms for data processing via tools available within the Hadoop ecosystem that will run on a physical and cloud cluster.
Kartik-Katkar / Image ProcessingThis GitHub repository serves as a valuable resource for researchers, developers, and enthusiasts working with AUVs, providing a range of image processing algorithms and tools tailored to enhance visual perception and analysis in underwater scenarios.
shaina-12 / Data Structures And Algorithms CodesThis repository is all about code that I have done during my classes of data structures using c, analysis and design of algorithms, operating system etc. It is as a helping guide for solving coding questions. I hopw you will like it.
Jando93 / Sentinel 1 Unsupervised Burned Area DetectionThis code represents a processing workflow for the unsupervised detection and mapping of burned areas using SAR Sentinel-1 (S-1) satellite data (https://sentinel.esa.int/web/sentinel/missions/sentinel-1). It was developed by implementing ESA-snappy (https://senbox.atlassian.net/wiki/spaces/SNAP/pages/24051769/Cookbook) for image pre-processing and Scikit-learn (https://scikit-learn.org/) for processing and classification. It consists of the following fundamental main steps: [A] using ESA-snappy: 1) open raw S-1 data; 2) S-1 pre-processing; backscatter Time-Average for pre- and post-fire period; 3) calculation of the SAR indices [burn difference (RBD), the logarithmic RADAR burn ratio (LogRBR), the delta radar vegetation index (ΔRVI) and the dual dual-polarization SAR vegetation index ΔDPSVI); 4) gray-level co-occurrence matrix (GLCM) texture features calculation. [B] Using Scikit-learn: 5) principal components analysis (PCA) transformation; 6) silhouette score analysis to set the k parameter value; 7) unsupervised classification using the k-means algorithm.
