Model Registration : Should it happen in training or deployment phase?
MLOps is a new, exciting field. With excitement comes uncertainty and with uncertainty, debates emerge. And healthy debates are good for growing the knowledge base of a...
Machine Learning Model Profiling in Azure Machine Learning
Architecting for Machine Learning involves many moving parts. From Machine Learning System Design, we know that ML Lifecycle is broadly categorized into two workflows...
Managed Online Endpoints in Azure Machine Learning
Before we introduce Managed Online Endpoints in Azure Machine Learning, let’s revisit deployment in Azure Machine Learning. For real-time model deployment in Azure...
Introducing Machine Learning System Design
Why do we need Machine Learning System Design? In their seminal paper, Hidden Technical Debt in Machine Learning Systems, Google researchers expound that only a small...
A must have trait in a Data Scientist
What is the most important trait/skill a Data Scientist must have? This question does rounds all over the information technology world these days. And answers may be...
Musings on Data Quality
Introduction For a successful Machine Learning or Data Science practice, the following elements are key: Business Case Quality Data Skilled Teams Technology Risk...
Evolution of Business Decision Making – From Humans to AI Driven
Practical life is all about Decisions. Often, we are at crossroads, and we need to decide about the next course of action. This is truer in the business world, where...
Azure Databricks and Azure Machine Learning make a great pair!
The two pillars of the Azure AI platform are Azure Databricks and Azure Machine Learning. And, this is a common debate in Azure AI circles. Naturally, the question...
Data Profiling in Power BI (using Azure Databricks)
In Microsoft, there are two worlds i.e. MS Azure and MS Office 365. They are two two different Active Directories in Microsoft world. Hence, they have their own tools to...
Elements of a Data Science practice
For a successful Machine Learning or Data Science practice, the following elements are key: Business Case Quality Data Skilled Teams Technology Risk Management Business...