Data Lifecycle in Production: Defining and Collecting useful data. How do we determine the criteria for “good” and “useful” data? Where can we collect the data from? How much data should we collect?
Machine Learning Roadmap — Part 1: Personal Recommendations for Beginners Think of it as starting out as a level 1 character. Try to understand the basic game mechanics, the environment and your allegiance. As y...
How to Start Your Data Journey? | Results from LinkedIn Polls Someone trying to start their ML journey would be confused about where to start. There are thousands of roadmaps in the world, some…
How to Maximize ML Project Success with Efficient Scoping? | MLOps 5 Scoping a Machine learning project is a very essential step as around 60–85% of the industrial AI projects fail every year. Get an idea…
MLOps 4: Data in production You have likely used chatGPT. Imagine how thoroughly the data was cleaned for the model. Let’s delve deeper into production data…