hardware inventory management using ML

Keywords: Harware Inventory,Machine learning,regression,Prediction

Background

Retailer store hardware inventory plays a important role in warehouse management for several industries. This management system helps to track warehouse details by using this information can ensure that there is an amount of goods are available or not . This paper discuss the above procedure by using the machine learning models. In this study purpose of the application was which country stores the large amount of data in data ware house .The information in the dataware house can be updated automatically by connecting through the networks. In this document a detailed graphical representation of the document can be shown from this representation can know information about the data warehouses in different countries . Hardware Inventory management must include a regression task.So various algorithms used by the author in this case study are Random forest regressor, Linear regression, Decision tree and KNN regression

Aim & Objectives

Aim
The main aim of this project is for visualizing the data which is stored in the data ware houses of different countries.
Objective
• Data Cleaning and pre-processing
• Data visualization
• Build the machine learning model

Research Methodology

various regression algorithms like KNNR,SVR,DT,RF and XGBOOSt

Software & Tools

Jupyter, Google Collab

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