Going beyond .fit()

bridging the gap between shallow implementation and deep reasoning behind Machine Learning

Welcome to our space,

we , beyond .fit() aims to create a learning space to enable the easier way of understanding and implementing niche ML/DS concepts and use-cases.
we use this term “.fit()” to denote the abstracted way of ML implementations.


We aspire to bring something beyond such abstractions. We hope our resources would help the learns in an effective way

~ TEAM

Our Inventory

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Brix

Beginner friendly Resources, Tutorials and Roadmaps

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Blox

Analysis and Studies around ML and DS Algorithms

Illustration

Blitz

Case Studies and Solution Designs on Interesting Problem Statements

Unveiling the Power of Neural Networks: A Dive into Machine Learning

The Fundamentals of Neural Networks When it comes to machine learning, few algorithms rival the powe…

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