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ModelOps(Model Operations)

There is a very thin line between ModelOps and MLOps. ModelOps is the next stage of MLOps where focus is more towards automating, retraining, and maturing mo…

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ITOps (IT Operations)

With the introduction of the big data era, it became impossible to manually manage those. ‘ITOps focuses on the best in practice IT operations.’ A few main a…

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AIOps(Artificial Intelligence Operations)

AIOps was initiated by Gartner in 2016. It supports DevOps, DataOps, MLOps, DLOps and ITOps together. AIOps came to surface after the inception of Big Data e…

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Data Science vsData Mining

These are one of the most confusing terms in the data domain. Both are mostly confused with each other. The major difference between both is. Data Mining is…

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Machine Learning vs Deep Learning

We all know what Machine Learning (ML) models are right? ML is about using raw but structured or semi-structured dataset, then creating feature tables which…

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Supervised vsUnsupervised Learning

Supervised and Unsupervised Learning categorizes the dataset into two where there are situations where sometimes we know or sometimes, we don’t know what’s i…

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AI vs Data Science

In the current era, people are confused between AI vs Data Science. ‘This is a very controversial topic.’ If you are clear about Data Science, then understan…

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Data Algorithms

To understand Data Algorithms, let's quickly know what an algorithm is. It is a procedure consisting of multiple steps with a set of instructions for a desir…

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Data Splitting forData Science

As the name says itself, Data Splitting is about dividing data into multiple datasets which can be for multiple departments, for multiple regions, for multip…

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Feature Table inML Modelling

This Feature is not that traditional feature 😊. Here, we will be discussing Feature which is an integral part of Data Science activity. I am sure non-data s…