Category: Data Science

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 rime 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...

Data Profiling options in Azure

The first step of Data Science, after Data Collection, is Exploratory Data Analysis(EDA). However, the first step within EDA is getting a high-level overview of how the...