Time_Series_Analysis_Forecast

Time Series Analysis for House Prices -- various methods: ARIMA variations, RNN and Prophet

Table of Contents

• Project Aim
• Dataset
• Libraries
• Models Selection

1. Project Aim

Time Series Analysis Project using different statistical and machine learning tools to descibe and forecast time-series data.

2. Dataset

The dataset ma_lga_12345.csv. It is the sales data of houses and flats in quarterly periods. The sale data in column MA.

3. Libraries

• Arima and Sarimax: numpy, pandas, statsmodels, pmdarima

• RNN: numpy, pandas, keras, statsmodels

• Prophet: to be added

4. Models

• The development of the ARMA, ARIMA model: differencing, checking for non-stationary data, auto-correlation, partial auto-correlation, seasonality, forecasting
• Development of sequence RNN models: to be added
• Development of forecasting with FB Prophet library: to be added