Travel Data by ARIMA

data analysis

This project deals with Time Series Problem to predict the number of passengers in a train over the next 7 months

The project focuses on predicting electricity load demand using the ARIMA model, a widely used time series forecasting technique.

Time Series analysis on INR vs USD using Holt WInter, explonential smoothing and ARIMA

Time Series Analysis and Forecasting with Python.

ai hackhaton

We have all heard the countless Bitcoin backers claiming that Bitcoin is a bullet-proof hedge against inflation and is the best way to protect long-term wealth, and recently many established financial institutions have also been hoping onto this bandwagon. Their argument is simple. Bitcoin, unlike normal fiat currencies, has a limited, predeterm…

The "Cincinnati Traffic Crashes - Time Series Analysis" is a comprehensive study that employs statistical techniques to examine patterns and trends in traffic accidents over time within the Cincinnati area. This analysis aims to forecast future incidents, and assist in developing strategies to enhance road safety.

Streaming data management and time series analysis using R

Python codes for time series forecasting

Learned time series analysis from Quantstart

The NIFTY 50 is a benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange. We use real-time dataset to calculate the stock predictions for future years.

Forecasting the monthly Sales of Shampoo for next 6 months using various models Linear Regression, Naive Approach, Simple Average, Moving Average, Simple Exponential Smoothing,Double Exponential Smoothing, Triple Exponential Smoothing ARIMA and SARIMA Models in Python.

The increasing demand for energy is one of the biggest reasons behind the integration of solar energy into the electric grids or networks. To ensure the efficient use of energy PV systems it becomes important to forecast information reliably. The accurate prediction of solar power variation can enhance the quality of service. This integration of…