Lack of operational excellence threatens us, not AI
Your business's biggest threat isn't the rise of AI, but the lack of operational excellence, a problem that new technology will only amplify.
coding, data science, ml, cloud, greentech
Your business's biggest threat isn't the rise of AI, but the lack of operational excellence, a problem that new technology will only amplify.
Learn practical strategies for innovation, prototyping, and creating data-driven products from AWS experience. Explore the Working Backwards framework and real-world examples of successful prototyping.
There's a myth that the stock market underperforms under Republican presidents. Does data support this claim? We analyze S&P 500 returns to test this popular belief.
The article describes a framework on how to run and implement a data science project
How e-commerce sellers, such as Amazon, Shopify, Temu and etc. can optimise the prices and have a higher revenue and profit. Price elasticities and A/B techniques can really make a big impact on your earnings.
The article shares a hands on example on an application of causal inference, double ML and Bayesian inference.
This is what happens to your website traffic when your post makes to the front page of tech news aggregators like HackerNews and Reddit . It appears that my previous post struck a nerve, sparking extensive discussions on these platforms. In this article, I’ll share my experience, key takeaways, and, most importantly (or perhaps not at all), whether it translated into any financial gains. Just in…
Throughout much of the 20th century, frequentist statistics dominated the field of statistics and scientific research. Frequentist statistics primarily focus on the analysis of data in terms of probabilities and observed frequencies. Causal inference, on the other hand, involves making inferences about cause-and-effect relationships, which often goes beyond the scope of traditional frequentist…
A view from a Tesla charging station in Germany
Lately, reading the news and following updates about advancements in AI, specifically in Generative AI and chatGPT, gave me mixed feelings - on one hand, we are on something big and impactful, but at the same time it feels like a potential threat to the future. And I’m not alone - NLP students lost their field of research overnight, meanwhile some orgs at FAANG became obsolete. It is an old news…