Machine Learning and Data Science applied to Manufacturing Processing
Learn to develop a machine learning project to real world problems in manufacturing processes
Updated on Jul, 2024
Language - English
Data Science and AI ML,Machine Learning
Lectures -20
Duration -2.5 hours
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Course Description
In this course, you are going to learn how to develop a machine learning project to solve real-world problems that you can find in the manufacturing area.
You will learn the more practical and useful algorithms that can help you to do predictions and work with big data.
If you are not familiar with machine learning and manufacturing, don't worry, because, in this course, you will learn the necessary to understand these manufacturing areas and machine learning thinking, so easily you will apply these techniques to this field.
And as we know, the best way to learn is making, so we will develop a project using python, in which we are going to analyze a real production power plant and we are going to develop different machine learning in order to predict the production of electricity based on various variables.
So, get started in machine learning with this amazing course and start to learn a bit about how machine learning can improve the manufacturing world.
Goals
- How to apply machine learning techniques to real world problems in the area of manufacturing
- Learn to implement useful and popular machine learning algorithms
- Learn what manufacturing processing is
- Learn about supervised and unsupervised machine learning approaches
- Learn to train a machine learning model
- Learn how to apply machine learning to a power plant
- Learn how a real data analysis project is developed
- Learn how to work with data files and load for data analysis
- Learn how to use free python libraries for machine learning
- Learn how to use jupyter notebook as a tool to develop a machine learning project
- Get valuable insights from data analysis and build a report
Prerequisites
- Basic knowledge of Python is required in order to understand the analysis (but I explained you all the code we are developing)
- No previous knowledge in Machine Learning is required
- No previous knowledge in manufacturing is required
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to Manufacturing processes
4 Lectures
-
Introduction
00:28
00:28
-
Introduction to Unit operations
04:48
04:48
-
Control and monitoring systems of processes
04:47
04:47
-
Production measurements in production plants
01:31
01:31
Introduction to Machine Learning
5 Lectures
Explanation of the study case
2 Lectures
Data exploration of the study case
3 Lectures
Machine learning models applied to study case
4 Lectures
Building a report with the insights of data analysis
1 Lectures
Summarize course
1 Lectures
Instructor Details
Leonardo Bravo
I am a Chemical Engineer and Master in Data Science. Actually I am working with deep learning applied to Astronomical data! It's crazy but it's fun too.
I love to teach and I always have been doing classes. I started doing classes at University (for a master course) and then, doing classes in other universities and private classes.
I also love to build things, especially digital things, so for that reason, I love to program and build software (mobiles, web and now, deploy machine learning models).
I hope you can enjoy my courses, and if you have any doubt, you can contact me.
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