Practical Insights Into Applying Double Lasso
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Practical Insights Into Applying Double LASSO.
Today causal inference is the goal of many applications of machine learning in economics. Double LASSO (Belloni, Chernozhukov & Hansen 2014) is one of the most widely used approaches. It transforms the causal inference problem into two prediction problems on the reduced form so that a standard variable selection method - LASSO (Tibshirani 1996) - can be applied to select the controls for each. These controls together are used to obtain the causal estimate with OLS. We review the performance of Double LASSO in settings that are realistic for applied work. We demonstrate both the circumstances in which Double LASSO may outperform simple benchmarks when the standard unconfoundedness assumption holds, how this out-performance may diminish when it does not and that biases may instead be amplified.
Navigating Barriers to AI Implementation in the Classroom
As artificial intelligence (AI) technologies advance, their potential to transform education is promising. From personalized learning to intelligent tutoring systems, AI offers tools that enhance student engagement and streamline administrative tasks. However, implementing AI in the classroom comes with challenges. Educators, administrators, and policymakers must navigate barriers, including limited technical infrastructure, data privacy concerns, lack of teacher training, and equity access across schools. Understanding and addressing these obstacles ensures that AI enhances educational equity rather than increasing existing divides. Further exploration may reveal key challenges and identify strategies for integrating AI into classroom practice. Navigating Barriers to AI Implementation in the Classroom investigates the ways in which AI alters education by streamlining administrative tasks, introducing new individualized learning opportunities, and transforming instructional strategies. It examines the capabilities of AI in education, including intelligent instruction, automated assessments, data-driven insights, adaptive learning systems, and ethical issues related to its employment in classrooms. This book covers topics such as classroom management, policymaking, and student engagement, and is a useful resource for educators, computer engineers, policymakers, academicians, researchers, and scientists.
A practical approach to clinical arrhythmology
The book is devoted to clinical arrhythmology and is written in a practical and understandable manner, intended for young cardiologists who sometimes get lost in the complexities of the field and fail to organize their knowledge in an efficient way. With this goal in mind, a number of prestigious specialists in the field have collaborated in this joint venture, writing a number of concise, useful, and very interesting chapters that summarize many hours of work and professional dedication. The result is easy to read and easy to handle. Perhaps best of all, this is an opportunity for the reader to enjoy a very personal celebration of friendship and electrophysiology.