After getting a lot of traction on one of my previous blog on full stack data science: The Next Gen of Data Scientists Cohort, I decided to start a blog series on Data Science in production. This series will go over the basics of the tech-stack and techniques that you can get familiarized with to face the real data science industry for specializations such as Machine Learning, Data Engineering, and ML Infrastructure. It will be a walkthrough of how you can take your academic projects to the next level by deploying your models and creating ml pipelines with best practices used in the industry. This is second part in the series and you can have a look at the first part here: Data Science in Production: Building Flask APIs to serve ML models with Best Practices
This blog will go over how you could quickly build interactive web applications which uses machine learning and how to deploy those applications into Heroku cloud. Anything showcase-able on your resume adds 10x more value than something which is just text.