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: 

1. You will learn how to import, explore, analyse and visualize your data.
2. 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. 
3. 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.
4. You will learn how to evaluate and measure the performance of your models with different metrics like: accuracy-score and confusion matrix.
5. You will learn how to compare between the results of your models.
6. You will learn how to fine-tune your models to boost their performance.

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