ABLIR_Artificial_Intelligence_Report.pdf

Artificial Intelligence Precious Julia Ablir COE 434  Table of contents 01 02 03 Introduction Fundamentals Machine Learning to Artificial Intelligence of Artificial Intelligence Techniqu...

Artificial Intelligence Precious Julia Ablir COE 434  Table of contents 01 02 03 Introduction Fundamentals Machine Learning to Artificial Intelligence of Artificial Intelligence Techniques 04 05 06 Deep Learning Applications Ethical and Neural Networks of Artificial Intelligence Considerations of AI 4 PICS 1 WORD 2 PICS 1 WORD 4 PICS 1 WORD ARTIFICIAL INTELLIGENCE Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.  AI Capabilities Problem Solving and Natural Language Learning Decision Making Processing  AI can mimic and even surpass human cognitive abilities in a wide range of applications.  01 Fundamentals of Artificial Intelligence  Fundamentals of AI Machine Knowledge Natural Language Learning Representation Processing Oh! I see Then make your a pattern! predictions! Machine Learning - enables systems to learn and improve from experience without being explicitly programmed.  Knowledge Representation - involves modeling and encoding information that can be processed and manipulated by computers, such as through the use of rules and logical reasoning. Natural Language Processing Roast my pretty face… in Bisaya. Gwapa diay allows systems ka? to understand, interpret, and generate human language. Machine Learning Techniques Machine Learning Techniques Supervised Learning Reinforcement Learning Unsupervised Learning Supervised Learning Supervised learning involves training an AI model using labeled data, where the desired output is known. Example of Supervised Learning Training Testing Prediction Labeled Dataset triangle triangle circle rectangle square rectangle Unsupervised Learning Unsupervised learning enables AI systems to discover hidden patterns and structures in data without the need for labeled inputs.  Example of Unsupervised Learning Unlabeled Data Machine Results Reinforcement Learning Reinforcement learning is a type of machine learning where an AI agent learns by interacting with an environment and receiving rewards or penalties for its actions.  Example of Reinforcement Learning State Reward Agent Environment Action Deep Learning and Neural Networks Artificial Neural Networks Artificial neural networks are a powerful class of machine learning models inspired by the structure and function of the human brain. These networks are composed of interconnected nodes, or neurons, that can learn to recognize patterns and make predictions from large datasets. Deep Learning Deep learning is when a computer is trained to recognize patterns by looking at lots of examples. The more examples it sees, the better it gets at recognizing things. Neural Learning Neural networks are the computer's brain, helping it recognize patterns by passing information through different layers. Applications of Artificial Intelligence Healthcare Manufacturing Education Automobile Business Security Ethical Considerations  Ethics of AI Transparency Impartiality Accountability Reliability Security Privacy  Summary Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. The fundamentals of AI include Machine Learning, Knowledge Representation, and Natural Language Processing.  Summary Machine Learning Techniques comprise supervised, unsupervised, and reinforcement learning. Applications of AI include healthcare, education, automobile, business, and security.  Summary Ethical consideration is vital when creating machines driven by artificial intelligence. The ethics of AI entails transparency, impartiality, accountability, reliability, security, and privacy.  References Image Sources: bsmedia.business-standard.com gstatic.com/images peakpublisher.net thenextweb.com venturebeat.com medium.com Simplilearn.com https://blog.get-merit.com/ slrlounge.com https://www.mdpi.com/1424-8220/22/18/6759 https://blogs.nvidia.com/ https://towardsdatascience.com/ Information Sources: https://www.ccbcmd.edu/Programs-and-Courses- Finder/course/CSIT/259.html https://www.prolific.com/resources/what-are-ai-ethics-5-principles- explained https://www.enjoyalgorithms.com/blogs/supervised-unsupervised-and- semisupervised-learning https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial- Intelligence https://www.linkedin.com/pulse/what-difference-between-supervised- unsupervised-learning-mrinal-walia http://neuralnetworksanddeeplearning.com/ https://www.slideshare.net/slideshow/presentation-on-artificial- intelligencepptx-de07/266844409 Thank you! Do you have any questions? CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, and infographics & images by Freepik Please keep this slide for attribution