Introduction to Machine Learning, Deep Learning and Distributed Training

Learn machine learning fundamentals, deep learning concepts, and distributed training techniques in this comprehensive lecture delivered as part of the Fast Radio Transient Sky (FTSky) 2025 program. Explore the theoretical foundations of machine learning algorithms and understand how deep learning architectures can be applied to astronomical data analysis. Discover distributed training methodologies that enable efficient processing of large-scale datasets commonly encountered in fast radio transient research. Gain insights into how artificial intelligence and machine learning techniques are revolutionizing the detection and analysis of cosmic phenomena such as Fast Radio Bursts (FRBs), magnetars, and other transient astronomical sources. Understand the practical implementation of these computational methods within the context of modern astrophysics research, particularly focusing on their application to time-domain astronomy and the processing of multi-wavelength observational data from radio telescopes and survey programs.