Timestamps:
00:00 Topic Introduction
01:34 A Simple Picture of Supply Chain
02:23 Our Task
02:46 Factors that Influence Demand
04:46 Time Series Features
05:48 Understand the Data
09:39 Choose the Right Error Metric
12:04 Diversify your Ensembles
13:21 Our Results
13:35 Build Your Own ML Forecasting Models
15:04 Q1 Which metric do you use for which purpose?
16:21 Q2 What about outliers?
17:24 Q3 How about packages for automatically generating time series features?
La Kopi @ Developers Space is a monthly open mic night for the developer community to learn, connect, and be inspired by each other. Every month, a tech theme is selected and developers submit their topics to be shared with the community.
Name: Silvia Lara (Data Scientist, LinkedIn)
Topic: Forecast Your Products’ Demand with Machine Learning
Do you have experience with Machine Learning but do not know how to get started with time-series data? Or maybe you want to scale up your demand forecasting efforts and increase your accuracy? We will explore how to build an effective Machine Learning forecasting model that reflects your business context.
You will learn how to design features, choose the most relevant error metric, validate your model to future-proof your accuracy, and how to decrease your errors through ensembles. Most importantly, you walk out from this talk with a framework to build any forecasting model.
Be our next La Kopi Speaker → https://goo.gle/openmic
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