NFC signal and protocol analyzer using SDR receiver

:link: Methods for Correlation Analysis

This repository contains the pytorch code for the 2023 ICASSP paper "Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting”

Open-source investment analytics platform bridging academic research and retail finance. Features include portfolio risk decomposition [Fama-French Five Factor Model], retirement sustainability modeling [Block Bootstrap Monte Carlo], max drawdown/CVaR dashboards, and risk-return optimisation [Markowitz, Ledoit-Wolf] via an intuitive user interface.

:bar_chart: 数据挖掘常用算法：关联分析Apriori算法，数据分类决策树算法，数据聚类K-means算法

A professional, research-grade comparison of Gaussian Copula and Variational Autoencoder (VAE) methods for synthetic tabular data generation. Includes full evaluation pipeline with distribution overlap, correlation analysis, PCA projections, pairplots, metrics, and automated visual reports.

A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant Olist.

correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations

Analyze financial news sentiment and its correlation with stock market movements. Use NLP, sentiment analysis, and financial analytics to uncover insights for enhanced financial forecasting and innovative investment strategies.

Blazing fast Gene/GEM Correlation Analysis for Rust and Python

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Open-source statistical package in Python based on Pandas

Twitter is an online social networking service with over 300 million monthly active users. This enormous amount of data available on social media platforms can be extracted and analyzed for various purposes. In this paper, we aim to investigate the relationship between sentiment analysis of Twitter data and stock market prices for five companies (Walmart, ExxonMobil, Apple, Berkshire Hathaway Inc., and Amazon) by scraping the Tweets extracted from Twitter based on company hashtags and using the twitter intelligence tool – twint. Sentiment analysis is applied to the extracted tweets and a correlation is analyzed between stock market movements of a company and sentiments in tweets. Elaborately, news and tweets in social media about a company would encourage decision of people to invest or not in the stocks of that company and as a result, the stock price of that company would increase or fall. At the end of the paper, it is shown that a none or very weak correlation exists between the rise and fall in stock prices with the public sentiments in tweets

以化学工业反应为例的因果门控时间序列神经网络 / Causal gated time series neural network based on chemical industry reaction

Time-Series Modeling of Bitcoin for Equities, Commodities & Forex Markets

collection of utility functions for correlation analysis

A code tutorial to accompany https://link.springer.com/article/10.3758/s13428-023-02098-1

In this repository, four famous correlation algorithms have been implemented. Pearson, spearman, Chatterjee, and MIC correlation algorithm implemented

A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn

PCA Insights is a data analysis project aimed at applying Principal Component Analysis (PCA) to high-dimensional datasets for dimensionality reduction, visualization, and exploration.

St. Nicolas House Algorithm implementation in R - predicting correlation networks using association chains

Exploring Google Play Store apps dataset to identify key factors for app engagement and success, revealing correlations between reviews, installs, categories, ratings, and user preferences.

Analysis of the relationship between environmental factors and diarrheal disease incidence across four major divisions in Bangladesh using machine learning models and time series analysis.

This repo is an attempt to diagnose Parkinson's disease using voice measurements of patients using machine learning algorithms.

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Assignment-11-Text-Mining-01-Elon-Musk, Perform sentimental analysis on the Elon-musk tweets (Exlon-musk.csv), Text Preprocessing: remove both the leading and the trailing characters, removes empty strings, because they are considered in Python as False, Joining the list into one string/text, Remove Twitter username handles from a given twitter text. (Removes @usernames), Again Joining the list into one string/text, Remove Punctuation, Remove https or url within text, Converting into Text Tokens, Tokenization, Remove Stopwords, Normalize the data, Stemming (Optional), Lemmatization, Feature Extraction, Using BoW CountVectorizer, CountVectorizer with N-grams (Bigrams & Trigrams), TF-IDF Vectorizer, Generate Word Cloud, Named Entity Recognition (NER), Emotion Mining - Sentiment Analysis.

A powerful tool for analyzing correlations between cryptocurrency tokens. Generate correlation matrices and visualize them through a web interface.

Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.

[IEEE TCSS 25]Devising PoPStat: A metric bridging population pyramids with global disease mortality

Computational protemics analysis of cancer cell-lines at the level of single-cells