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AI Engineering Management: Exploratory Data Analysis (EDA) in Python — Understanding Data

PART III — AI Engineering Management

Mahmudur R Manna
13 min readDec 5, 2024

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Prior Discussions:

PART I — AI Engineering Management: Is There a Methodology for AI Model Development?

PART II — AI Engineering Management: Estimating Effort for AI Model Development

Non-member Link:

https://mrmanna.medium.com/ai-engineering-management-exploratory-data-analysis-eda-in-python-understanding-data-7b70ea986d0f?sk=b530fbaed000b6291a6ed6b5bc2ffc20

Introduction

Exploratory Data Analysis, or EDA, is the gateway to understanding data. It’s where you uncover patterns, detect anomalies, and validate hypotheses, setting the foundation for robust data-driven decisions. Whether you’re building machine learning models or presenting insights to stakeholders, EDA ensures you approach your data with confidence and precision.

Why Python?
Python has become a cornerstone of the data analysis ecosystem, thanks to its powerful libraries and flexibility. While tools like R, SAS, and Tableau are popular for EDA, Python offers a unique blend of simplicity and extensibility. It empowers developers and analysts alike to manipulate data…

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Mahmudur R Manna
Mahmudur R Manna

Written by Mahmudur R Manna

Engineer | Author | Entrepreneur with over two decades of experience across the globe at the intersection of technology and business

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