This repo holds the details about different model build to predict wine quality.
The following are the tools that are covered in the notebooks. They are popular tools that machine learning engineers and data scientists need in one way or another and day to day.
Python is a high level programming language that has got a lot of popularity in the data community and with the rapid growth of the libraries and frameworks, this is a right programming language to do ML.
NumPy is a scientific computing tool used for array or matrix operations.
Pandas is a great and simple tool for analyzing and manipulating data from a variety of different sources.
Matplotlib is a comprehensive data visualization tool used to create static, animated, and interactive visualizations in Python.
Seaborn is another data visualization tool built on top of Matplotlib which is pretty simple to use.
Scikit-Learn: Instead of building machine learning models from scratch, Scikit-Learn makes it easy to use classical models in a few lines of code. This tool is adapted by almost the whole of the ML community and industries, from the startups to the big techs.