All Posts

Why data quality is key to successful ML Ops

Are you testing your data in your data pipeline 🧪?

Why Best-of-Breed is a Better Choice than All-in-One Platforms for Data Science

Interesting view from O’Reilly on why Best-of-Breed trumps All-in-One data science platforms ‼️

Roadblocks to Production Vary for Different Roles

Roadblocks to model production vary for different roles 🚧

The Recession's Impact on Analytics and Data Science]

We have all felt the impact of the recession in one way or another.

How to Bridge Missed Opportunity

You hired 5x ML Professionals, but you are not getting 5x the return.

How to Bridge Missed Opportunity

Found a beautiful and clean illustration from Valohai on MLOps Stack.

Which Age of MLOps Are You In?

It’s 2020 - which “Age” of MLOps are you in❓

With AI, You Either Go Big or Go Home

Most companies choose to start with building small scale PoCs or POVs.

O'Reilly: What you need to know about Product Management for AI

Product managers have a tremendously tough job.

Considerations for Deploying an ML Model

✈ Deploying a machine learning model is like flying an airplane 🛩 Having no logging is like flying without a Blackbox.

WORKERA: AI Career Pathways

There is an emergence of two types of AI focuses within an organisation according to WORKERA:

O'Reilly: 5 key areas for tech leaders to watch in 2020

According to O’Reillly online learning platform report, summarising the AI/ML:

Build Things Properly

A couple of days ago, we had a meeting to help a client operationalise their machine learning model.

Pandas is finally version 1.0

Can you believe Pandas 1.0.0 is finally here?

Algorithmia: 2020 state of enterprise machine learning

Hello 2020! We started the year by reviewing this white paper published by Algorithmia on the 2020 State of Enterprise Machine Learning.

McKinsey: Global AI Survey

This study from McKinsey suggested that there have been measurable benefits from deployed AI.