Testing Machine Learning Models
In machine learning, testing is mainly used to validate raw data and check the ML model's performance. Learn more about it in our guide. (more…)
Read more »Upscale Images With Machine Learning
Learn how to enhance images using Filestack’s transformation API.
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How Machine Learning Is Being Abused
“If world is already talking about it, then it’s already obsolete.” -Donald Knuth...
Read more »Interpretability in Machine Learning: A Broad Overview
This blog post is my attempt to give an overview of the sub-field of machine learning interpretability. I do not intend for this post to be necessarily comprehensive, but my goal is to review conceptual frameworks, existing research, and future directions... (more…)
Read more »Machine Learning 102: Logistic Regression with Polynomial Features
How to classify when there are nonlinear components... (more…)
Read more »Machine Learning in Haskell
Much advocacy of Haskell, in general, boils down to type-safety and elimination of bugs. How boring. My personal experience is that bugs are trickier in Haskell and I can write bad code in an extraordinary variety of ways. I don’t code in Haskell to help ... (more…)
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