Blog
Is it worth it? The cost of better AI
As data scientists, we always strive to be accurate in our machine-learning/AI models, i.e., provide better predictions or improved responses to prompts (user queries). As
Unveiling the Hidden Patterns of Health: A Personal Data Exploration Journey
Join us on a fascinating journey into the depths of personal data exploration, where Alex, a curious data scientist, delves into the intricacies of his
Visualizing Variable Relationships: A Guide to Correlations & Correlograms
Correlations in data science unravel a rich tapestry of relationships among variables—positive, negative, and nuanced connections. Dive into how correlograms wield visual power, offering a swift glimpse into complex datasets, guiding initial analysis. But remember, while they illuminate pathways, further research unveils the complete narrative within your data.
About game theory in kindergarten parties
Friday mornings are our guilty pleasures (for my wife and me). You see, in Israel, Friday is an off day, and the kids are in
DIY tools in Market Research: Benefits and Problems
The DIY trend (“Do It Yourself”) has overtaken the world. It’s everywhere, and market research is not any different. Companies increasingly turn to DIY techniques
How machine learning is used in social networks?
My daughter just turned 9. A few months ago, she asked me to uninstall the TikTok app from her mobile phone. TikTok started showing her videos of animal abuse, probably because its recommendation algorithm thought it would increase her viewing time. How is that related to machine learning though…?
What is Data Science? (and how it can help in your business)
Data Science is a relatively new scientific field. It started developing in the last decade and intermixes statistics, mathematics, and computer science. Data Science mainly
What dinosaurs are hiding in your data?
One of the important tools data scientists love using are data visualizations (i.e., graphs). You might be asking yourself why can’t we completely rely on descriptive statistics? Shouldn’t average, standard deviation, correlation be enough? well… they aren’t.