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Dark Matters
Machine learning research, op-eds, and news from Ensemble.
Unobserved Confounders: How Admitting What We Don’t Know Can Unlock Data’s Full Potential
Unobserved confounders have long been considered a limiting factor in the accuracy of statistical models, but machine learning’s ability to approximate underlying patterns in data ...
The Limitations of LLMs: Why Simple Models Still Outperform in Most Use Cases
LLMs and deep learning are highly effective in some contexts, but most industry use cases are still better addressed by traditional ML models. We discuss ...
Redefining Data Quality: A Paradigm Shift in the Machine Learning Pipeline
Data quality issues form some of the central challenges in machine learning, but what do we mean by “quality”? Here we redefine and reframe the ...
Case Study: stuffmart.com Customer Conversion
TL;DR Background This case study focuses on predicting customer conversion in the online retail space using real-world customer behavior data and enhancing these predictions with ...
Ensemble Raises $3.3M Seed Round Led by Salesforce Ventures to Accelerate Machine Learning Experimentation
SAN FRANCISCO, CA – [SEPTEMBER 9th, 2024] – Ensemble, a company dedicated to lowering barriers to state-of-the-art machine learning (ML), today announced it has raised ...
Case Study: Banking Customer Churn Prediction
TL;DR Background “Churn” refers to the rate at which customers halt their business with a company. This case study focuses on predicting churn in the ...
Case Study: Kinase Cancer Inhibitor Dataset & Performance
Background When selecting a dataset for a case study in biotech, it was important to find something unique to the domain. Ideally, we utilize a ...
