In order to deepen knowledge in the field of machine learning and artificial neural networks, PUI-PT Combinatorics and Graphs invited Dr. Nagamani Gnaneswaran of Gandhigram Rural Institute India. Nagamani presented material entitled "Introduction to Artificial Neural Networks". Nagamani explained that artificial neural networks (ANN) are mathematical models inspired by biological neural networks in humans. ANN has several advantages such as learning ability, adaptive ability, small fault tolerance, and low energy consumption. The architecture of neural networks is divided into feed forward nets, competitive nets and recurrent nets. Nagamani added that there are two types of feed forward nets, namely single layer nets (if you only have 1 hidden layer) and multi-layer nets (if you have more than 1 hidden layer). Based on the learning machine learning is divided into 3 types: supervised learning, unsupervised learning, and reinforcement learning. ANN itself is included in supervised learning. Prof. Drs. Dafik, M.Sc., Ph.D. We hope that this guest lecture can add to students' knowledge in the field of machine learning, especially ANN. In the future Prof. Dafik also hopes to establish joint research between the University of Jember and the Gandhigram Rural Institute.

This webinar also available on youtube with this link: (350) GUEST Lecturer Series: Dr Nagamani Gnaneswaran. K - YouTube