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. What would be the impact of the shrinking economy on analytics and data science?
How to Bridge Missed Opportunity
You hired 5x ML Professionals, but you are not getting 5x the return.
MLOps Stack
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. Unfortunately, with this approach, many struggled to move from experimentation to scale. According to Michael Gale at the recent Nvidia virtual GTC conference: starting small means staying small.
O'Reilly: What you need to know about Product Management for AI
Product managers have a tremendously tough job. An AI product managers does everything a traditional PM does, and much more .
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. Any terrorist can hijack the plane without any consequences.
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: