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
Learn, practice, and apply job-ready skills with expert guidance
Beginner level
Recommended experience
2 hours
Learn at your own pace
Hands-on learning
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
Skills you'll practice
- Predictive Modeling
- Artificial Neural Networks
- Machine Learning Algorithms
- Data Analysis
- Decision Tree Learning
- Applied Machine Learning
- Machine Learning
- Random Forest Algorithm
- Data Manipulation
- Exploratory Data Analysis
- Python Programming
- Deep Learning
- Regression Analysis
- Statistical Methods
- Data Visualization Software
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
No downloads or installation required
Only available on desktop
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Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies
About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Understand the Problem Statement and Business Case
Practice Opportunity #1 [Optional]
Import Libraries/Datasets and Perform Data Exploration
Practice Opportunity #2 [Optional]
Perform Data Visualization
Practice Opportunity #3 [Optional]
Prepare the Data for Model Training
Train and Evaluate a Linear Regression Model
Train and Evaluate a Decision Tree and Random Forest
Practice Opportunity #4 [Optional]
Understand the Theory and Intuition Behind Artificial Neural Networks
Train an Artificial Neural Network to Perform Regression Tasks
Practice Opportunity #5 [Optional]
Compare Models and Calculate Regression KPIs
Capstone Final Project
Recommended experience
basic python programming
15 project images
Instructor
Offered by
How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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Frequently asked questions
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.