40 skills found · Page 1 of 2
zhaokg / RbeastBayesian Change-Point Detection and Time Series Decomposition
elena-roff / Time Series ProphetTime Series Analysis & Forecasting of Rossmann Sales with Python. EDA, TSA and seasonal decomposition, Forecasting with Prophet and XGboost modeling for regression.
GeneSUN / Time Series Analysis ToolkitA comprehensive toolkit for time series analysis, including scripts for visualizing results, detecting stationarity, trends, seasonality, and heteroscedasticity, as well as building models, and evaluating performance
Hazrat-Ali9 / Bike Sharing Demand Forecasting Using Time Series Analysis⚽ Bike ⚾ Sharing 🥎 Demand 🏀Forecasting 🏐 Time 🎮 Series 🥌 Analysis is 🎳 a data ⛸ science ✈ focused on 🚁 predicting 🚀 bike 🛸 demand 🚟 time 🚠 series 🚞 techniques ⛴ analyzing 🚢 historical 🚒 bike 🛺 weather 🚋 data 🚂 seasonal 🚃 trends this 🚅 helps 🏩 optimize 🏦 planning 🕍 resource 🏠 allocation 🕌 and 🔐 operational 🪣 efficiency 💶
Madhuarvind / Retail Sales AnalysisA complete exploratory data analysis (EDA) and forecasting project focused on retail sales data. The project identifies key sales patterns, seasonal trends, and builds predictive models to forecast future demand at the item-store level.
vdrakopoulou / Sentiment Analysis BUS2503 AI For BusinessH&M Seasonal Campaign Sentiment Analysis – Case Study & Replication Package for BUS2503 / AI for Business using KNIME, Python, and LLM ChatGPT as a co‑tutor.
jahangirmammadov / SarimaEconometric Approach to Time Series Analysis — Seasonal ARIMA in Python
Kommandat / Seasonality Fourier AnalysisAnalyzing seasonality with Fourier transforms
blab / Global MigrationAnalysis of global migration patterns of seasonal influenza viruses
mrcmich / Deep Seasonal Color Analysis SystemA deep system for seasonal color analysis and palette-based clothing retrieval.
pushkarsaini18 / Gold Price ForecastingGold-Price-forecasting In a personal endevaour to learn about time series analysis and forecasting, I decided to reserach and explore various quantitative forecasting methods.This notebook documents contains the methods that can be applied to forecast gold price and model deployment using streamlit, along with a detailed explaination of the different metrics used to evaluate the forecasts. Goal: The goal of this project was to predict future gold price based on previous gold price. I apply various quantitative methods, (i.e. Times Series Models and Causal Models) to forecast the Price of the gold available in the dataset obtained from Kaggle. Models covered in the Project include: 1.Naive Model 2.ARIMA and Seasonal ARIMA Models 3.Linear Regression Model 4.Model Deployment (Streamlit)
DavidCico / Univariate Time Series Analysis Of Cryptocurrency Data With ARIMA And SARIMA And Hypergrid SearchTwo Jupyter Notebooks written in Python, treating of time series analysis with ARIMA and its seasonal counterpart.
Nelvinebi / Sea Surface Temperature SST Analysis For Climate StudiesThis project simulates and analyzes synthetic Sea Surface Temperature (SST) data to demonstrate climate study techniques, including trend analysis, seasonal decomposition, and anomaly detection. It serves as an educational tool for understanding climate change indicators through time-series analysis using Python.
mwtoews / Seasseas Package for R: Seasonal Analysis and Graphics, Especially for Climatology
pruggerd / Structural Vector Autoregression ModelingI analyze the interplay of three U.S. time series: unemployment, inflation and gross domestic product. The first cleans the data and invests seasonality and stationarity. The second part develops a (structural) vector autoregressive model and test structural identification. The third uses principal compnent analysis and three different quality criterions to forecast quarterly U.S. GDP.
whitelightning450 / Machine Learning Water Systems ModelThis machine learning workflow demonstrates a framework to function a digital twin of a systems dynamics model for urban water system seasonal water system reliability, resilience, and vulnerability analysis.
samad-00 / Excel ProjectAn Excel-based interactive dashboard built using pivot tables, charts, slicers, conditional formatting, and KPI indicators to analyze India’s multi-year agricultural crop yield dataset. The project includes data cleaning, preprocessing, seasonal analysis, state-wise contribution comparison, year-on-year yield growth, and dynamic visual reporting.
iskandergaba / PyriodicityPyriodicity provides an intuitive and efficient Python implementation of periodicity length detection methods in univariate signals.
asupraja3 / Retail Ts AnalysisRetailTS is a data visualization and exploratory analytics project focused on uncovering trends, patterns, and seasonal behaviors in retail sales using time series analysis techniques.
MoinDalvs / Forecasting Airline Passengers TrafficForecast the Airlines Passengers. Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for Forecasting.
