Don’t Make the Same Mistake I Have Made in a Machine Learning Project!

Author(s): Sai Viswanth

Originally published on Towards AI.

Realized the crucial component in a machine learning project
Photo by Pierre Bamin on Unsplash

Often more than not we don’t consider it at all.

I learned it the hard way from my internship experience.

My journey began when I started learning the fundamentals of machine learning back in college, I used to do a lot of projects to get a deep understanding of how things work.

It helped to get a headstart compared to others, as it enhanced my knowledge to apply these concepts to real-world applications.

But without realizing it, I have fallen into a cycle of vicious traps such that unconsciously, I kept repeating it in every project. I was so centric and focused on:

Which Machine learning Model to use?Increase Performance using optimization strategies.Invest time in EDA analysis.Various techniques in cleaning data.

This list keeps on going till the very end of this article. And I do agree with you that these are essential in building a high-performance model.

But looking at the broader picture, the above steps are generally the same in every machine learning project. So, What do you think changes are considered important for every project?

DATA CHANGES EVERYTHING !!!!

Photo by Markus Spiske on Unsplash

When the data changes — the strategies to clean the data change, visualization graphs used to find… Read the full blog for free on Medium.

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Published via Towards AI