On 2023-03-06 I shared with my class colleagues some concepts and examples about AI, Machine Learn, and Deep Learn. It was amazing and we discussed how a machine can identify a Tiger, a common animal from India. (Thank you Ravi Rawat for your comments).
Artificial Intelligence (AI) is a broad field that involves the development of machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. AI systems use algorithms to analyze and process data, learn from patterns and experiences, and make predictions or decisions based on that learning.
Deep learning is a subset of machine learning that is inspired by the structure and function of the human brain. It involves the use of artificial neural networks, which are composed of layers of interconnected nodes that process information and learn from examples. Deep learning algorithms are particularly effective for tasks that involve large amounts of data, such as image or speech recognition, natural language processing, and autonomous driving.
Deep learning has been used in a variety of applications, such as medical diagnosis, fraud detection, image and speech recognition, and language translation. However, it also has some limitations, such as the need for large amounts of training data and computational resources, and the difficulty of interpreting the decision-making processes of deep learning models.
Overall, IA and deep learning are rapidly evolving fields with numerous applications in various industries. As technology continues to develop, we can expect to see further advancements and improvements in AI systems and their ability to perform complex tasks.
Thank you, Professor Iyad Koteich for this opportunity.