Remove Data Preparation Remove ETL Remove Exploratory Data Analysis
article thumbnail

Turn the face of your business from chaos to clarity

Dataconomy

It ensures that the data used in analysis or modeling is comprehensive and comprehensive. Integration also helps avoid duplication and redundancy of data, providing a comprehensive view of the information. EDA provides insights into the data distribution and informs the selection of appropriate preprocessing techniques.

article thumbnail

How to Use Exploratory Notebooks [Best Practices]

The MLOps Blog

And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. When data science was sexy , notebooks weren’t a thing yet.

SQL 52
article thumbnail

Building ML Platform in Retail and eCommerce

The MLOps Blog

The objective of an ML Platform is to automate repetitive tasks and streamline the processes starting from data preparation to model deployment and monitoring. In this section, I will talk about best practices around building the Data Processing platform. are present in the data. How to set up an ML Platform in eCommerce?

ML 59