Predicting Walmart Sales and Performing Exploratory Data Analysis
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Updated
May 18, 2024 - Jupyter Notebook
Predicting Walmart Sales and Performing Exploratory Data Analysis
Sales Forecasting for next 36 months
Auto ARIMA Model
Time Series Analysis model application
This is simple workflow for predicting the future usuage of energy demand based on time series analysis with Auto ARIMA.
Stonks Rabbi is a streamlit-based application that uses the Yahoo Finance API to visualize and analyze stock trends, patterns, and performance over its listed time period. The metadata is handled through pymongo, the frontend is on streamlit, and autoARIMA, pandas, and matplotlib are used for data analytics and visualization.
food retail shops forecast
Find stock price in real time
Learn ML 2021 challenge of prediction of closing prices of 5 stocks for each day with features open, high, low, close, Volume weighted average price, turnover
Prediction of road casualties and evaluate the impact of transformations in Time Series Modeling and Forecasting with ARIMA using the R programming language
Analysis and Prediction of Ethereum Prices and Its Correlation with Other Assets.
With the help of the stats models in python forecasting the future values
Time Series Analysis of Airline Passenger Data, In this time series forecasting, taking data from kaggle site and applying ARIMA and SARIMAX model to evaluate seasional trends of passenger travelling via airlines.
Projeto do curso Criando modelos com Python e Machine Learning para prever a evolução do COVID-19 no Brasil
This repository contains a Jupyter notebook that demonstrates time series analysis and forecasting using ARIMA, auto-ARIMA, and Prophet. Time series analysis is a powerful tool for understanding and predicting future trends, and these techniques are widely used in a variety of fields such as finance, economics, and marketing. The notebook is based
Univariate timeseries forecasting in the browser (ARIMA)
Julia Package with SARIMA model implementation using JuMP.
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