Bias-variance tradeoff
The bias-variance tradeoff is essential in machine learning, impacting how accurately models predict outcomes. Understanding this tradeoff helps practitioners optimize their models, achieving a balanc...
Mean absolute percentage error (MAPE)
Mean absolute percentage error (MAPE) is a crucial metric in the realm of data analysis, particularly for those engaged in forecasting. It allows analysts to quantify how well a prediction model perfo...
Binary classification
Binary classification plays a pivotal role in the world of machine learning, allowing for the division of data into two distinct categories. This binary decision-making capability is at the heart of n...
CI/CD for machine learning
CI/CD for machine learning is transforming how organizations develop and deploy machine learning models. By integrating continuous integration and continuous deployment practices, teams can streamline...
Training-serving skew
Training-serving skew is a significant concern in the machine learning domain, affecting the reliability of models in practical applications. Understanding how discrepancies between training data and ...
Altman and Nadella are now fighting over AI
Sam Altman and Satya Nadella, once at the helm of a thriving partnership between OpenAI and Microsoft, are increasingly at odds over the terms of their collaboration, according to a recent article pub...
IBM just made one of its biggest bets ever on US tech
IBM has pledged to invest $150 billion in the U.S. over the next five years, with a significant portion dedicated to advancing its research in mainframe and quantum computing. The tech giant aims to f...
