Machine/Deep Learning for Mining Quality Prediction-Enhanced

Overview

In this hands-on project, we will train machine learning and deep learning models to predict the % of Silica Concentrate in the Iron ore concentrate per minute. This project could be practically used in Mining Industry to get the % Silica Concentrate at much faster rate compared to the traditional methods.

Syllabus

Project Overview

In this hands-on project, we will train machine learning and deep learning models to predict the % of Silica Concentrate in the Iron ore concentrate per minute. This project could be practically used in Mining Industry to get the % Silica Concentrate at a much faster rate compared to the traditional methods. In this hands-on project we will go through the following tasks: (1) Understand the Problem Statement, (2) Import libraries and datasets, (3) Perform Exploratory Data Analysis, (4) Perform Data Visualization, (5) Create Training and Testing Datasets, (6) Train and Evaluate a Gradient Boosting Regressor Model, (7) Train and Evaluate a Decision Tree Regressor Model,(8) Train and Evaluate a Random Forest Regressor Model, (9) Train and Evaluate an Artificial Neural Network Model, (10) Calculate and Print Regression model KPIs.