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.
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SKILLS YOU WILL GAIN
Machine Learning
Predictive Modelling
Data Cleaning
Data Visualization
WHAT YOU WILL LEARN
Build machine learning models to do classification tasks
Build, Train, Test, Evaluate and Fine-Tune machine learning models