Time Series Analysis in Python Tutorial - V1

Publié le: 21 décembre 2020
sur la chaîne: Yiannis Pitsillides

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Learn how to run Time Series Analysis Forecasting in Python. In this tutorial, we go over 4 different forecasting models; Arima, Auto Arima, Prophet and Regression. We also go through how to tune / improve your Arima model manually or automatically. Later on in this series, we go through how to deploy your time series forecasting model in Power BI.

Support the channel on Patreon:
  / data360yp

Data Analytics Course Link:
http://ipidata.teachable.com/

Video Part 1:
• What is a Time Series Model?
• Importing / Installing packages
• Problem Formulation - What are we trying to solve?
• Reading / Loading the Raw Data into Python From CSV
• Data Pre-Processing Phase
• Splitting the Raw Data
• Running Arima (Autoregressive Integrated Moving Average) - 1 Country
• Parameter Tuning
• Running Auto-Arima
Video Part 2:
• Running Prophet
• Running Arima & Auto-Arima Together
• Running Arima, Auto-Arima, Prophet & Linear Regression Together
• Storing the outputs all together
• Fixing bugs in for loops
• Running all models on all countries
• Combining actuals with predictions
• Exporting the Data
Video Part 3:
• Power BI

Data Analytics Course Link: http://ipidata.teachable.com/

GitHub repo:
https://github.com/Pitsillides91/Pyth...

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