Categorical Features: When to drop a column while OneHotEncodingThis article gives an explanation for dropping a column while OneHotEncoding. The intended audience is familiar with programming in python…Mar 14, 2021Mar 14, 2021
Guide to Linear Regressions in PythonThis article outlines the essentials to define a linear regression in python using numpy.Mar 6, 2021Mar 6, 2021
Creating a Pipeline with SklearnThis article is a brief overview of what a data pipeline is, why it is useful, and how to create one for a classification model. The…Feb 28, 2021Feb 28, 2021
Creating GIFs from MRI Scans (nii.gz)This article is intended for those proficient in Python with image data in the neuroimaging data format nii.gz looking to convert into an…Feb 21, 2021Feb 21, 2021
Exploring Matplotlib’s ColormapsThis article explores the various colormaps Matplotlib provides, it is intended for readers proficient in Python with exposure to…Feb 12, 2021Feb 12, 2021
Data Science 101: Creating the Perfect Confusion MatrixThis article outlines the Python code to create a confusion matrix visualization function and explores the different colormaps available…Feb 7, 2021Feb 7, 2021
Confusion Matrix: Friend or Foe?This article describes the process of understanding confusion matrix in the context of data science model analysis.Jan 31, 2021Jan 31, 2021
A Simple Guide to Linear Regressions with Polynomial FeaturesAs a data scientist, machine learning is a fundamental tool for data analysis. There are two broad classifications for machine learning…Jan 28, 2021Jan 28, 2021
GUIs in Python: TkinterThis article provides a general overview of the use and purpose of Tkinter.Jan 27, 2021Jan 27, 2021
To sklearn, or to not sklearn?This article is a friendly overview of this paper on scikit-learn published in volume 12 of the Journal of Machine Learning Research…Dec 12, 2020Dec 12, 2020
