Machine Learning Lifecycle

In business management, product lifecycle is broken into 4 stages with the distinct pattern of sales over time: introduction, growth, mature, and decline. In the diagram below, I adapt the classic product lifecycle curve to show the engineering load over time in machine learning (ML): from model development to maintenance. Managing and coordinating different stages in ML lifecycle presents pressing challenges for ML practitioners. 

Onboarding as a Machine Learning Engineer

It’s been 3 months since I started my new position as a Machine Learning Engineer (MLE) at Spotify. What I like most about this position is that I get to participate in building an end-to-end pipeline, including ideation and experiment, data engineering, machine learning modeling, model serving, online A/B test, monitoring, and many more. 

Tips for first-time mentors from a first-time mentor

This summer, I volunteered to be a mentor for a data science intern. It reminds me of my own internship 2 years ago, when I learned so much from my mentor (see my previous posts). Being a mentor not only allows me to view a summer internship from the other side of the table, but also presents new challenges and learning opportunities for myself. In this post, I will share some tips for first-time mentors from my experience as a first-time mentor.