With the .com boom of late 90’s and early 2000’s and wide adoption of email across the World, capturing the attention of users through an email was fairly easy compared to the current saturated digital space. Increasing volume of promotional content within...
A subtle selection bias in machine learning-based causal inference can flip your results — here’s how to spot and fix it Machine learning is great at predicting outcomes. But when we try to use it to estimate causal impact, especially in a two-stage setup,...
Due to the recent advancements in artificial intelligence (AI) and machine learning (ML), organizations are increasing investments in information technology (IT) infrastructure that best supports automation enabled by AI and ML. While these automated systems can guide...
When I joined a B2B SaaS startup in 2021, I was transitioning from a bigger and more mature company. In my previous company, I was working on a particular area of the product – while it was rigorous and intense – I was excited...
Ana Arias, Geographic Information Systems Analyst at the City of Coral Gables, was a speaker during the DSS MIA 2024 conference. Her talk about transforming public services using AI was an inspiring and refreshing session between business- and technology-focused...
Regression is one of the most important techniques in predictive modelling. It is usually the gateway into the world of data science and machine learning, offering a perfect balance of simplicity and power. Whether you're forecasting next month's sales figures or...
In our previous post, we introduced Linear Regression, a fundamental technique used to predict outcomes based on a single factor—such as estimating house prices based on square footage. We also discussed essential performance metrics like Mean Squared Error (MSE) and...
In the digital age, where data accumulates boundlessly, distilling complex datasets into comprehensible and compelling narratives isn’t just beneficial, it’s indispensable. This article ventures through the realm of data visualization, highlighting the fusion of...
In a world where data availability is becoming increasingly abundant, how can we leverage multiple data sources to answer questions of scientific interest? This matter is a perfect spot to use the entity resolution. What is entity resolution? Why does it...
The main difference between data science and business analytics is their focus and application. Data science involves the extraction, analysis, and interpretation of large datasets to gain insights and make data-driven decisions. It utilizes various statistical...