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.
Machine/Deep Learning for Mining Quality Prediction-Enhanced
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Train Artificial Neural Network models to perform regression tasks
Understand the theory and intuition behind regression models and train them in Scikit Learn
Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, adjusted R2
Details to know
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Assessments
1 assignment
Taught in English
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There is 1 module in this course
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.
What's included
1 reading1 assignment1 ungraded lab1 plugin
Instructor
Offered by
Recommended if you're interested in Machine Learning
Johns Hopkins University
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
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