Author: Gregory Morris
Data science can be defined as the scientific study of data to gain knowledge. This field combines multiple disciplines to extract knowledge from massive datasets for the purpose of making informed decisions and predictions. Data scientists, data analysts, data architects, data engineers, statisticians, database administrators, and business analysts all work in the data science field.
Top Skills & Pay of Data Nerds
A checklist of steps and code cheat sheets, although not all-inclusive. The goal is to remind or inspire you when going through the process of a Data Science (DS) project. Organized so that you can reference the information and code you need on the step you need it.
Remember that DS is the hammer and Machine Learning (ML) is the nail, NOT the other way around.
A how-to guide to learning DS. Explanations are often minimal and it is assumed the reader will seek additional information to better understand concepts and code.
These are 8 steps that you have to perform in almost every DS project. The steps should be seen as iterative with many not truly belonging to their own category. I have categorized them nonetheless for easy reference.
Review the first page of each section as you go through the stages of your project. Each page serves as a reminder of concepts and considerations.
Optional: Within each chapter see the section noted with </> for additional information and code relevant to the topic. These sections were added to reduce searching the web for related material.