How Wrong Is Your Model?
In this blog, we look at the topic of uncertainty quantification for machine learning and deep learning. By no means is this a…
In this blog, we look at the topic of uncertainty quantification for machine learning and deep learning. By no means is this a…
This post follows up on the series of posts in Topic Modeling for text analytics. Previously, we looked at the LDA (Latent Dirichlet…
It is no secret that GPUs are critical for artificial intelligence and deep learning applications since their highly-efficient architectures make them ideal for…
Sentiment analysis is commonly used to analyze the sentiment present within a body of text, which could range from a review, an email…
This post is the third in a series on Bayesian inference ([1], [2] ). Here we will illustrate how to use managed MLflow…
This post is part of a series of posts on topic modeling. Topic modeling is the process of extracting topics from a set…
In a previous post, we looked at how to use PyMC3 to model the disease dynamics of COVID-19. This post builds on this…
The Chief Data Officer (CDO) is not a new position – Capital One reportedly had a CDO all the way back in 2002.…
Machine learning has proved to add unprecedented value to organization and projects – whether that’s for accelerating innovation, personalization, demand forecasting and countless…
In this post, we look at how to use PyMC3 to infer the disease parameters for COVID-19. PyMC3 is a popular probabilistic programming…