Practitioner lectures, unlike conventional public lectures conducted by permanent university faculty, are delivered by non-permanent lecturers from professional domains. These lectures typically span one semester or consist of a limited number of face-to-face sessions. The focus of this discussion revolves around a specific practitioner lecture titled “Application of Artificial Neural Networks to Image and Text Classification Using PyTorch”.
This practitioner lecture, held both offline for students enrolled in the Artificial Neural Networks course and online via Zoom meetings for external participants, took place at LKMATH 6, Faculty of Science and Technology, Universitas Airlangga on Wednesday, November 16, 2022, from 15:00 to 17:00. The lecture was conducted by Syahrul Hamdani, M.Si, an alumnus of the class of 2012, currently serving as a Data Scientist.
During the session, Syahrul elucidated on the application of artificial neural networks utilizing PyTorch, a deep learning tensor library optimized for Python and Torch. Renowned for its adeptness in GPU and CPU applications, PyTorch distinguishes itself from other deep learning frameworks, such as TensorFlow and Keras, through its utilization of dynamic computational graphs and complete Python integration.
Presently, PyTorch stands as the preferred artificial intelligence (AI) library among researchers and practitioners globally, across both industrial and academic sectors. Syahrul underscored PyTorch’s versatility, highlighting its applicability across various disciplines, including Calculus, Mathematical Statistics, Optimization, Data Structures, and even Algebra. PyTorch’s utility extends to tasks such as optimal equation determination, result analysis, model evaluation, and algebraic matrix operations, rendering it an indispensable tool in academic pursuits and practical applications alike.
In light of the insights shared, the prospects of delving into PyTorch appear notably intriguing and worthy of exploration.
