
If you want to get the course's slides file in PDF (for free) to support your learning process, you can subscribe here and I will send you the material:
https://forms.gle/ZeNuNPBTxbqXX3VXA
The data set link:
https://archive.ics.uci.edu/ml/datasets/Combined+Cycle+Power+Plant
If you do not have "Jupyter notebook", you can download "Conda" (it's a software that contains all the required libraries in the course (included Jupyter notebook)):
https://docs.conda.io/projects/conda/en/latest/user-guide/install/
If you do not want to use it, you are going to need a text editor. I recommend you:
- Sublime ( https://www.sublimetext.com/ )
- Visual Studio ( https://visualstudio.microsoft.com/ )
And then install all the libraries we are going to use. So you should install:
- python
- numpy
- pandas
- matplotlib
- sklearn
All these resources are for free!
If you want to get the course's slides file in PDF (for free) to support your learning process, you can subscribe here and I will send you the material:
https://forms.gle/ZeNuNPBTxbqXX3VXA
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.