[Day 196] Learned about 'ML canvas' and more about MLOps
Hello :) Today is Day 196! A quick summary of today: Today I found this great resource for MLOps. Below I will summarise the posts I read A better pic of the above is on my repo . I learned about the above 'ML Canvas' concept from the below resources. Motivating MLOps Why MLOps? Machine learning (ML) models are increasingly being used in production environments, but their development and deployment are often disconnected from traditional software development and operations practices. This disconnection leads to various pain points, such as: Lack of collaboration: Data scientists, engineers, and operators work in silos, leading to inefficiencies and errors. Inconsistent workflows: Ad-hoc processes and manual interventions hinder reproducibility, scalability, and maintainability. Inadequate infrastructure: Insufficient infrastructure and tools lead to difficulties in deploying, monitoring, and updating ML models. Motivation for MLOps To address these challenges, MLOps aims to b...