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Optical spectroscopy and imaging techniques play important roles in many fields such as disease diagnosis, biological study, information technology, optical science, and materials science. Over the past decade, machine learning (ML) has proved promising in decoding complex data, enabling rapid and accurate analysis of optical spectra and images. This review aims to shed light on various ML algorithms for optical data analysis with a focus on their applications in a wide range of fields. The goal of this work is to sketch the validity of ML‐based optical data decoding. The review concludes with an outlook on unaddressed problems and opportunities in this emerging subject that interfaces optics, data science, and ML.

In article number 2000422, Yuebing Zheng and co‐workers review the advances of machine learning (ML) in decoding complex optical data, enabling rapid and accurate analysis of optical spectra and images. ML‐assisted optical data decoding can shorten the data analysis time by skipping the intermediate segments and provide an insight into the unknown physics. Recent progress has been discussed with a focus on applications in disease diagnosis, noninvasive biological study, information technology, fundamental studies in optics, and materials science and engineering.

Moiré chiral metamaterials (MCMs) consisting of stacked plasmonic nanohole arrays with twist angles exhibit strong chiroptical response, thereby opening doors to ultrathin chiroptical sensors, switches, and detectors. The existing fabrication of MCMs on the basis of colloidal lithography results in significant inhomogeneity within the structure, which impairs the responsiveness and tunability of its optical chirality. Here, we develop thermal-tape-transfer printing to enable the fabrication of large-scale and homogeneous MCMs with arbitrary twist angles and tunable optical chirality. As a demonstration, large-scale (100 × 100 μm2) gold MCMs with an ultrathin thickness (∼40 nm) were fabricated, which marked a 10-fold increase in single domain size over the colloidal lithographic method, while showing spatially uniform and strong chiroptical response. With the ultrathin thickness and high tunability, the MCMs developed by our fabrication method will advance a variety of biological, photonic, and optoelectronic applications.