Discussion 2

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 Compare and contrast neural networks with their biological equivalent. Be sure to consider both the function and structure at the level of a single neuron and that of the entire network. Hello class, Neural networks are a subset of machine learning that teaches computers to process data through algorithms which are modeled after the human brain ( What Are Neural Networks? | IBM , 2024). Artificial and biological neural networks share the fundamental concept of processing information through interconnected neurons or nodes ( What Is a Neural Network? - Artificial Neural Network Explained - AWS , 2024). In a biological neuron network, the structure of a single neuron consists of the cell body, dendrites, axons, and synapses ( Overview of Neuron Structure and Function (Article) | Khan Academy , 2024). The basic function of neuron is to receive signals (information) through the dendrites, the cell body integrate the incoming signal (determine if the information should or should not be passed), the axons then communicate to other neurons, and synapses connect are the neuron-to-neuron connection. A single neuron does not do much and a system of neurons in the human body like the central nervous system contains a group of neurons to make the system work. Artificial neural networks structures consist of neurons or nodes. A single neuron can only perform a simple task. Complex functions can be created by using a network of interconnecting neurons. Artificial neural networks as an entire network consists of a layered structure, with an input layer, an output layer, and one or more hidden layers (Yang, 2013). Artificial neural networks use mathematical equations through weighted graphs to learn when presented with sets of data (Yang, 2013). The difference between machine and human learning is humans have the ability to understand the context of things while machine learning lacks contextual understanding. Machine learning relies on patterns found in data they are trained on (Kaushik, 2023). Within human learning, we learn through sensory, cognition, and memory. Human learning is not limited to a set of data and can adapt and apply to a wide range of situations. For example, humans can drive, swim, and react to human social cues. In machine learning, generally they are tasked in solving specific tasks. Machine learning does not have the flexibility of learning different tasks as human learning. References Kaushik, H. (2023, September 22). Machine Learning vs Human Learning: The Battle for Future Dominance. Medium . https://medium.com/@himanshubangalore/machine-learning-vs-

human-learning-the-battle-for-future-dominance-fa7a1c99cd0c#:~:text=Machine %20learning%20algorithms%20lack%20contextual,a%20deep%20understanding%20of %20context. Overview of neuron structure and function (article) | Khan Academy . (2024). Khan Academy. https://www.khanacademy.org/science/biology/human-biology/neuron-nervous-system/ a/overview-of-neuron-structure-and-function What are Neural Networks? | IBM . (2024). https://www.ibm.com/topics/neural-networks What is a Neural Network? - Artificial Neural Network Explained - AWS . (2024). Amazon Web Services, Inc. https://aws.amazon.com/what-is/neural-network/#:~:text=A%20neural %20network%20is%20a,that%20resembles%20the%20human%20brain . Yang, X. (2013). Optimization and metaheuristic algorithms in engineering. In Elsevier eBooks (pp. 1–23). https://doi.org/10.1016/b978-0-12-398296-4.00001-5

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