This project is part of my phD thesis. The aim of this work is enable people of food science and technology area to work with Python for data science/chemometrics. Python could be used to analyze near infrared spectroscopy (NIR) or time domain nuclear magnetic ressonance (TD-NMR) data and build machine learning models to predict quality parameters using only the aquired instrumentation signal. This program could be used to fast evaluate outliers in datasets and train/test PLSR models.
Douglas William Menezes Flores douglasfloresm@gmail.com
PyCharm2019 Python 3.6; Xlrd 1.2.0; Openpyxl 3.0.0; Scikit-learn 0.21.2; Seaborn 0.9.0; matplotlib 3.1.0; Pandas 0.24.2; numpy 1.16.4; scipy 1.3.0; pip 19.1.1;