Implement Time Series Analysis for E-Commerce on Amazon Forecast, from scratch! - Brand New Workshop

Hey there CloudWolves!

Are you ready for our brand new AI in the Cloud workshop? This one will be epic and you will learn so much!

In this new lab, we will leverage the power of Amazon Forecast for Times Series Analysis in a real-world E-Commerce case study. We will build a Time Series Prediction model to predict the demand of products in a retail store based on their historical sales.

Amazon Forecast is a fully managed deep learning service for Time Series Predictions. By providing Amazon Forecast with historical time-series data, you can predict future points in the series. Time-series forecasting is useful in multiple domains, including retail, financial planning, supply chain, and healthcare. You can also use Amazon Forecast to forecast operational metrics for inventory management, and workforce and resource planning and management.

Prerequisites for this lab: Make sure you have an AWS account set up. Also just as a refresher, I recommend watching the following tutorials in our CloudWolf platform:

What is S3?
S3 Quick Win
Amazon Forecast [Hands-On]

Please find the dataset folder for this lab (Live Lab #12 - Datasets.zip) in our CloudWolf platform. Here is the description of the data inside this folder:

Tiny Data: 1 store, 3 items, 1 year (only 2017).
Small Data: 1 store, 3 items, 5 years (2013 to 2017).
Medium Data: 1 store, 50 items, 5 years (2013 to 2017).
Big Data: 10 stores, 50 items, 5 years (2013 to 2017).
Huge Data: 10 stores, 50 items, 5 years (2013 to 2017), training and test sets.

Looking forward to doing our new CloudWolf lab together!

Here are the timestamps of the video:

0:00 Welcome!
0:45 Presentation of the datasets
6:00 Amazon Forecast pricing
9:00 Amazon Forecast Intro: Create a dataset group
12:00 Store the data in S3
20:40 Amazon Forecast Step 1: Import the data
28:55 Amazon Forecast Step 2: Train a predictor
42:20 Amazon Forecast Step 3: Generate forecasts
53:45 Final Cleanup

Cheers,
Hadelin

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