Explore the concept of classical shadows in quantum states through this comprehensive lecture by John Preskill from the California Institute of Technology. Delve into an experimentally feasible procedure for converting quantum states into succinct classical descriptions. Learn how classical shadows can be applied to efficiently predict various properties of interest, including expectation values of local observables and few-body correlation functions. Discover how efficient classical machine learning algorithms utilizing classical shadows can address quantum many-body problems, such as classifying quantum phases of matter. Gain insights into shadow tomography, shadow norm, and their applications in ion traps and quantum chemistry problems. Examine numerical experiments and results related to quantum phases of matter, followed by a Q&A session and summary of key concepts.