Author Rajiv Shah

Introduction Cyber and malware analysts have a critical role in detecting and mitigating cyberattacks. These professions are highly skilled in programming, complex tools, and investigations. They are termed unicorns because they are so rare. Experienced ones are hard to find and retain, and typically swarmed with ad-hoc requests. A reliable partner for cybersecurity analysts is AI and machine learning. There…

“A wrecking-ball of a paper” -- this was Brandon Rohrer’s takeaway on a new paper, Underspecification Presents Challenges for Credibility in Modern Machine Learning by D’Amour, et al. Using a set of actual use cases, the paper articulates how machine learning often fails in the real world. But then the paper stops.   My customers have asked me what they should…

Machine learning is a glass cannon. When used correctly, it can be a truly transformative technology, but just a small oversight can cause it to become misleading and even actively harmful. Even if all the code runs and the model seems to be spitting out reasonable answers, it's possible for a model to encode fundamental data science mistakes that invalidate…

At the heart of machine learning is the identification of features or variables that are useful for a prediction. Without the right features, your model lacks the information required to make good predictions. Including redundant or extraneous features can lead to overly complex models that have less predictive power. Striking the right balance is known as feature selection. In this…

As someone who spends hours searching for new music, getting lost in rabbit holes of ‘related artists’ or ‘you may also like’ tabs, I wanted to see if cover art improves the efficiency of the search process. Browsing through a collection of images takes a lot less time than listening to clips of songs. As a starting place, I was curious if machine learning could accurately predict an album's genre from the cover art. In this post, I will show you how I built this model and what it teaches us about the role a record’s cover plays in categorizing and placing an artist's work into a musical context.

With the continued unfolding of the COVID-19 pandemic, the world’s economies and societies are going through an extended period of uncertainty. This ongoing volatility brings new challenges for organizations and teams managing predictive models.  It’s tricky to maintain a grip on production model management and monitoring under normal circumstances. The current turbulent times highlight this issue even further, with models…

The world is going through extremely turbulent times. With the ongoing disruption of our lives, communities, and businesses from the COVID-19 pandemic, predictions from existing machine learning models trained prior to the pandemic become less reliable. There is plenty of historical data, but historical examples from before the pandemic may not provide the relevant examples needed to train a model…

Data science teams are scrambling to update their models in the wake of extreme and unforeseen worldwide changes brought on by the global COVID-19 pandemic. In the face of these unprecedented events, one of the key concerns among many data scientists is that their current models could be generating inaccurate or misleading predictions. In the webinar, AI in Turbulent Times:…