Machine Learning in Physics: Glass Identification Problem

Move your ML skills from theory to practice in one of the most interesting fields " Physics"?

In this course, you are going to solve the glass identification problem where you are going to build and train several machine learning models in order to classify 7 types of glass( 1- Building windows float-processed glass / 2- Building windows non-float-processed glass / 3- Vehicle windows float-processed glass / 4- Vehicle windows non-float-processed-glass / 5- Containers glass / 6- Tableware glass / 7- Headlamps glass).

Through this course, you will learn how to deal with a machine-learning problem from start to end:

• You will learn how to import, explore, analyse and visualize your data.
• You will learn the different techniques of data preprocessing like data cleaning, data scaling and data splitting in order to feed the most convenient format of data to your models. 
• You will learn how to build and train a set of machine learning models such as Logistic Regression, Support Vector Machine (SVM), Decision Trees and Random Forest Classifiers.
• You will learn how to evaluate and measure the performance of your models with different metrics like accuracy score and confusion matrix.
• You will learn how to compare the results of your models.
• You will learn how to fine-tune your models to boost their performance.

After completing this course, you will gain a bunch of skill sets that allow you to deal with any machine learning problem from the very first step to getting a fully trained performant model.