AI

[ad_1] Prior to receiving a PhD in computer science from MIT in 2017, Marzyeh Ghassemi had already begun to wonder whether the use of AI techniques might enhance the biases…

[ad_1] When to be data-driven, and when data-driven just gets in the way.I was working as a data scientist at Airbnb when Covid-19 struck. And as you might expect, Covid-19…

[ad_1] Applying Reinforcement Learning strategies to real-world use cases, especially in dynamic pricing, can reveal many surprisesPhoto by Markus Spiske on UnsplashIn the vast world of decision-making problems, one dilemma…

[ad_1] The modern data stacks allow you to do things differently, not just at a larger scale. Take advantage of it.Photo by Massimo Botturi on UnsplashImagine you’ve been building houses…

[ad_1] Learn about main ranking algorithms for sorting search results12 min read·12 hours agoLearning to rank (LTR) is a class of supervised machine learning algorithms aiming to sort a list…

[ad_1] The number of large language models llms has been increasing since 2019 (See Figure 1) due to the models’ extensive application areas and capabilities. Yet, the estimates show that…

[ad_1] Discover Methodologies to Ensure Accuracy, Consistency and Completeness of Supply Chain DataWhat is Data Quality? — (Image by Author)Data Quality defines how data sets can be trusted, understood and…

[ad_1] Artificial neural networks, ubiquitous machine-learning models that can be trained to complete many tasks, are so called because their architecture is inspired by the way biological neurons process information…

[ad_1] Implementation of the XGBoost algorithm in Python from scratchImage by StockSnap from PixabayIn the previous article we discussed the XGBoost algorithm and showed its implementation in pseudocode. In this…

[ad_1] We're exploring the use of LLMs to address these challenges. Our large language models like GPT-4 can understand and generate natural language, making them applicable to content moderation. The…