How Model Monitoring Can Save You Millions of Dollars
Learn how to estimate post-deployment model performance, detect univariate and multivariate data drift and do a root cause analysis to find the underlying issue.
How Model Monitoring Can Save You Millions of Dollars
Learn how to estimate post-deployment model performance, detect univariate and multivariate data drift and do a root cause analysis to find the underlying issue.
All my dead projects
Collection of all the personal projects that I have worked on that are no longer active.
If I had to start learning Data Science again, how would I do it?
Self-study data science roadmap
Published on other sites
nannyml.com
91% of ML Models Degrade in Time
A recent study from MIT, Harvard, The University of Monterrey, and other top institutions showed an experiment where 91% of their ML models degrade over time.
nannyml.com
Monitoring Workflow for Machine Learning Systems
Introduction to a performance centric machine learning monitoring workflow.
nannyml.com
6 ways to address data distribution shift
Learn six different approaches to fix a model performance degradation issue due to data drift.
365datascience.com
How to Deploy Machine Learning Models with Python & Streamlit?
Building machine learning models is fun. But sharing them with the rest of the world is even more fun. In this tutorial, we will learn how to build a simple ML model and then deploy it using Streamlit. In the end, you will have a web application running your model which you can share with all your friends or customers.
towardsdatascience.com
Approaching Your First NLP Project
This article will help you cut through your first NLP project and end it with great results. We will be working with tweets data from the Disaster Tweets Dataset.
towardsdatascience.com
If I had to start learning Data Science again, how would I do it?
A couple of days ago I started thinking if I had to start learning machine learning and data science all over again where would I start? The funny thing was that the path that I imagined was completely different from that one that I actually did when I was starting.