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...
Akhil Theerthala
Generating adversaries for CNNs: My cat is a goldfish, so don’t tax it.
Adversarial Machine learning
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…
MLOps 3.3: Data-Centric Approach for Machine learning modelling.
Learn about the “Data-centric” machine learning modelling approach and its standard procedures here.
MLOps Notes 3.2: Error Analysis for Machine learning models
Ever wondered about the standard practices used for improving machine learning models or finding the right area to improve your models?