Machine Learning Analysis fundamentals in Retail
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Master machine learning fundamentals for retail analysis. Learn how to apply AI techniques to optimize inventory, pricing strategies, and customer insights to boost retail business performance.
At a Glance
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.
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, the dependencies found, 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
- Analyzing the impact of the price of goods in exporting countries and the domestic market price of the importing country
What you will learn
- Download a DataSet from *.csv files
- Create new and recalculate the values of existing columns
- Transform a table
- Join DataSets
- Visualize data with pandas and seaborn
- Make correlation analysis
- Apply basic methods of machine learning such as Linear regression and simple Neural Networks
- Calculate the accuracy of models
- Make forecasting
- Calculate the sensitivity of models
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