All Posts
5 Steps to Frictionless AI
How can we make AI frictionless?
What the Ops are you talking about?
How to choose between DataOps vs MLOps vs AIOps - what are the right Ops for your big data team?
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❓
Launching Into Uncertainty - 6 Smart Steps to Future-Proof Your ML Models
Your machine learning model is going to fail in the pandemic.
With AI, You Either Go Big or Go Home
Most companies choose to start with building small scale PoCs or POVs.
3 Tips You Need To Save Your Data Science Project Scope
Never spend another second building a monster-app that is miles away from the original scope.
O'Reilly: What you need to know about Product Management for AI
Product managers have a tremendously tough job.
Rise above the ordinary — a data science reading list
An hour reading sprint a day to keep your knowledge broad and up-to-date
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.
3 Tips on Defining a Data Science Project Scope with Business
Never be in trouble for delivering the wrong thing at the wrong time to the wrong person.
