Machine Learning Analysis fundamentals in Retail

This lab is dedicated to learning the basic Machine Learning methods for analysis of Retail based on Global Food Prices data from the World Food Programme covering foods such as maize(corn), rice, beans, fish, and sugar for 76 countries and 1,500 markets.

GPXX0D45EN

Artificial Intelligence

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Name: Machine Learning Analysis fundamentals in Retail
Rating: 4.0 (4 reviews)
Author: rav_ahuja, yaroslav_vyklyuk_2

This lab uses the basic methods of Machine Learning to predict prices in markets around the world. Three different types of forecasting prices for purchases are considered:

Establishment of functional relationships between groups of goods in the markets of a particular country. This is based on the found dependencies, the construction of the forecast and sensitivity analysis between price fluctuations for different groups of goods
Establishing relationships between prices in the different markets of a country
Analysis of the impact of the price of goods of exporting countries on the domestic market price of the importing country.

The main difficulty of analyzing real data is that they are prepared or presented in a form inconvenient for machine learning methods. There are no clear algorithms and rules for choosing machine learning methods for analysis.

This lab shows the use of a set of machine learning methods to solve these problems.

Offered By: IBM

Machine Learning Analysis fundamentals in Retail

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