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

Exploring Time Series in R - This is an exploration of time series analysis that includes moving average, holt-winters smoothing, and ARIMA models.

http://skillfactory.ru/ml-programma-machine-learning

Analizador de tráfico para dispositivos Android potencialmente comprometidos como parte de una botnet orientado a detectar ataques DDoS.

Forecasting the passengers on the train route

Time Series Analysis of Lake Erie Water Levels from 1921-1970 | Python

Android app testing reaction times during awake brain surgeries

bitcoin prediction algorithms

A time series forecasting project about the brief application of lstm(deep learning), prophet, arima, holt, exponential smoothing algorithms

A web application use machine learning method to predict the electricity consumption data

Forecasting Revenue for Kids Retail Store

Time Series Analysis & Prediction using Holt's Linear trend model and ARIMA model for comparison

Uses public information request data from https://github.com/fivethirtyeight/uber-tlc-foil-response/tree/master/uber-trip-data to map pick-ups to boroughs and forecasts rides.

Kaggle - Time-series Forecasting the optimal number of agents for a Contact Center: Facebook Prophet, InfluxDB Holt-Winter

Holt-Winters exponential smoothing implemented in Go.

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

The Repository contains Udacity's Nanodegree Program final project

TimeSeries-Analysis using Python

Using Holt-Winters, ARIMA and SARIMA model to predict the electricity consumption