Tuesday, May 13, 2025

Durgesh Kekare

I am a dedicated professional with a profound enthusiasm for the Data Science and Analytics field. With over 5 years of hands-on experience in the realm of data, I channel my expertise into insightful blogs and writing. My primary mission is to empower a discerning audience of analytics enthusiasts, assisting them in achieving their objectives and finding effective solutions through engaging and informative content. I firmly believe in the transformative potential of knowledge-sharing and the propagation of awareness in unlocking the full capabilities of analytics. Dive into my articles to embark on a journey of discovery within the dynamic and powerful world of Data Science.

How to Compile Python Code: A Beginner’s Guide to Python Compilers

Python is one of the most well-known programming languages. Python has several execution environments and is an interpreted programming language. To run Python applications, it offers a variety of...

Want to learn about Logistic Regression? Check it out here!

Applications in data mining and machine learning depend heavily on classification methods. Almost 70% of data science problems are classification problems. Logistic regression is a popular and practical regression...

Everything one needs to know about the Sigmoid Function

The sigmoid function is basic to the transformation and interpretation of data in the fields of machine learning and deep learning. Effective ML/DL model creation requires an understanding of...

Agentic AI vs Traditional AI: Why Businesses Are Making the Shift in 2025

Traditional ways are being replaced by Agentic AI in almost all industries by 2025. It was in the recent years Artificial Intelligence has altered the way businesses have managed...

How Artificial Intelligence Services Can Improve Your Business Goals

Today, artificial intelligence services are utilised in mundane business activities in various sectors like healthcare, finance, retail, and manufacturing. This is a significant change from the past, when only...