Predict the concentration of gold during the gold purification process

A machine learning model is being built for an industrial company that develops solutions for the efficient operation of industrial enterprises.

Creation of a model for predicting the recovery coefficient of gold from gold-bearing ore based on data with extraction and purification parameters.

Table of Contents

• General Info
• Technologies Used
• Project Status
• Room for Improvement

General Information

• Task: Predict the concentration of gold during the gold purification process.
• The purpose of the project: Using historical data, build a machine learning model predicting the concentration of gold in the ore after cleaning.
• The model will help optimize production so as not to launch an enterprise with unprofitable characteristics.

Technologies Used

• Pandas - version 1.3.5
• Numpy - version 1.21.6
• Sklearn - version 1.0.2
• Matplotlib - version 3.2.2

Project Status

Project is: complete

Room for Improvement

To do:

• Testing another ML models.
• Data analysis for the possibility of creating new features, identifying relationships between different stages of cleaning.