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the-prextics---preventive-maintanance-project

Problem Statement: In this Contest case study we work on data related to machine breakdowns to predict future occurrences and create a framework for preventive maintenance. The above machines work on the principal of pressure at 3 points. The company wants to build a model to predict breakdown and use preventive maintenance to reduce downtime (time during which production is stopped especially during setup for an operation or when making repairs).

time-series-data-analysis-for-global-mart

Business understanding: “Global Mart” is an online store super giant having worldwide operations. It takes orders and delivers across the globe and deals with all the major product categories - consumer, corporate & home office. Now as a sales/operations manager, you want to finalise the plan for the next 6 months. So, you want to forecast the sales and the demand for the next 6 months, that would help you manage the revenue and inventory accordingly. The store caters to 7 different market segments and in 3 major categories. You want to forecast at this granular level, so you subset your data into 21 (7*3) buckets before analysing these data. But not all of these 21 market buckets are important from the store’s point of view. So you need to find out 2 most profitable (and consistent) segment from these 21 and forecast the sales and demand for these segments.

time-series-forcast-using-r

In this assignment we were given to implement Linear regression model,Holt Winters model and Arima model to perform time series forecast of the stock price on the NASDAQ stock dataset. R programming was used to implement this model.

time-series-forecasting

This repository will show time series forecast plotting in both Python and R

time-series-forecating

Prediction of sales using Time series forecasting in R

time_series_forecasting

Time_series_forecasting in R using ARIMA,Auto ARIMA ,Arimax and Holt Winters

timeseriesprediction

Forecasting Stock Returns in R

timetk

A toolkit for working with time series in R

tsintermittent

:exclamation: This is a read-only mirror of the CRAN R package repository. tsintermittent — Intermittent Time Series Forecasting. Homepage: http://kourentzes.com/forecasting/2014/06/23/intermittent-demand-forecasting-package-for-r/

us-mortality-data-from-2006-2016

walmart-forecasting-nn

Walmart weekly sales forecasting, Missing data imputation, Neural network, Support Vector Machines

weekly_forecasting

Using TBATS model to accurately forecast sales for the next week with historical data of 104 weeks

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow