Council Post: Ensuring successful scaling-up strategy for your analytics product

Council Post: Ensuring successful scaling-up strategy for your analytics product

As per the International Data Corporation’s estimates, the global data volume would reach an astounding 175 zettabytes by 2025. To help you understand the magnitude a little better, it is 175, followed by 21 zeros! Not all of this data is useful and extracting business insights from huge swathes of data is akin to looking […]

A Beginner’s Guide to MLOps

With the fast development in the machine learning frameworks, comparative approaches are being created within the capacity of ML engineering, which handles the special complexity of the practical application of machine learning.

Top 10 Tools To Kickstart Your MLOps Journey In 2021

Top 10 Tools To Kickstart Your MLOps Journey In 2021

The MLOps market is expected to grow by almost $4 billion by 2025, according to analytics firm Cognilytica. Amazon, Google, Microsoft, IBM, H2O, Domino, DataRobot and Grid.ai have all incorporated MLOPs capabilities into their platforms.  Most companies are using MLOPs for automation pipeline, monitoring, lifecycle management, and governance. According to Algorithmia, last year, close to […]

Does MLOps Live Upto The Hype?

Machine Learning (ML) model metrics are designed to monitor performance. But when a model goes into production, many factors influence its performance. The traditional checkpoints may no longer help as organisations look to scale these models (think: scaling from a million to billion credit card users). This is why experts advocate for MLOps, a branch […]

MLOps Vs DevOps: A Comparative Analysis

Advances in machine learning and data science have led to the creation of new branches. The new specialisations are often rooted in the same basic principles and have overlapping functionalities. For example, MLOps and DevOps. In this article, we discuss why the two are different and cannot be used interchangeably. DevOps: Development + operations DevOps […]