ð Deep Learning for Physics – DELPHYS 2025
December 14 @ 8:00 AM – December 20 @ 5:00 PM
āļāļāđāļāļīāļāđāļāđāļēāļĢāđāļ§āļĄāļāļēāļĢāļāļāļĢāļĄāļāļāļīāļāļąāļāļīāļāļēāļĢāļāļēāļāļāđāļēāļ machine learning deep learning āđāļĨāļ° āļāļēāļĢāļāļĢāļ°āļĒāļļāļāļāđāļŠāļģāļŦāļĢāļąāļāļāļīāļŠāļīāļāļŠāđāļŠāļģāļŦāļĢāļąāļāļāļąāļāļĻāļķāļāļĐāļēāļ§āļīāļāļąāļĒāđāļāļĢāļ°āļāļąāļāļāļĢāļīāļāļāļēāļāļĢāļĩāļŦāļĢāļ·āļāļŠāļđāļāļāļ§āđāļē āļāļąāļāļ§āļīāļāļąāļĒ āļāļēāļāļēāļĢāļĒāđ
āļŦāļąāļ§āļāđāļāļāļēāļĢāļāļĢāļĢāļĒāļēāļĒ
– Basic programming in machine learning and deep learning.
– Supervised machine learning: regression and classification.
– Unsupervised machine learning.
– Deep learning: image processing and neural network.
– Applications in physics: time series data, cosmology.
āļ§āļąāļāļāļĩāđ 14 – 20 āļāļąāļāļ§āļēāļāļĄ āļ.āļĻ. 2568