Data Analysis and Python Universal Functions for Data Scientists: Part 2

Optimizing Workflows, Boosting Productivity, and Speeding up Feature Selection, Engineering, and Model Fitting In continuation of my exploration into Python functions for data scientists, particularly in the realm of data analysis and exploratory data analysis (EDA), I previously introduced a set of universal functions tailored for various scenarios, especially geared towards junior data scientists and newcomers in the field. In this post I will provide a more advanced set of universal functions crucial for the toolkit of senior data scientists. As professionals progress in their careers, the challenges evolve from exploratory analyses to the intricate task of building predictive models and gleaning profound insights from vast datasets. In response to these challenges, this paper introduces a collection of universal Python functions, proven to be indispensable for seasoned data scientists. These functions serve to streamline and optimize various stages of the modeling process, encompassing feature selection, engineering, data organization, and model fitting. For comprehensive information, kindly refer to the following post: https://medium.com/@datalev/data-analysis-and-python-universal-functions-for-data-scientists-part-2-af6bd46532dd