In this project, you will be learning all the basics of machine learning, many libraries and modules in Python. Specifically, we will be learning algorithms for Data Analysis such as Polynomial Regression, Logistics Regression, Supervised Learning Techniques, KNN algorithm , Dendrograms etc. The application for the study is the Descriptive analytics of Car data after performing the Data Cleaning.

In this project Adiabatic Flame Temperature(AFT) calculation will be performed using coding language Python and in-build Suite of Cantera. Cantera is an open-source suite of tools for problems involving chemical kinetics, thermodynamics, and transport processes. So, the comparative analysis will be performed to compare the factors like time requirement, accuracy etc. The effect of number of carbon atoms on Adiabatic Flame Temperature will also be discussed.

In this project, you will be using python to obtain data from a file that contains information related to a CFD simulation of an engine. The data is provided in the form of columns for different engine parameters. Based on user input, this data is then obtained from the file by using string splitting methods and converting strings to numerical data and saved in variables. A data visualiser is created such that the relationship between any two variables in the file can be plot with each other. Additionally, an engine performance calculator is created that provides the engine parameters.