Artificial intelligence is the core field which is the combination of different sub-domains: Programming skills + Innovative ideas+Neural Networks+Networking+Cloud Services. When we talk about Machine learning than we say it is based entirely on Programming methodology.
AI provides you the rational results which is trained through the process of training the the models and machines and therefore it is with the help of machine learning (python, R programming,Xolo)
When we are saying operational research than we are talking about the methodology of analytics. Currently R programming is been used efficiently for analytics.
Artificial intelligence is the core field which is the combination of different sub-domains: Programming skills + Innovative ideas+Neural Networks+Networking+Cloud Services. When we talk about Machine learning than we say it is based entirely on Programming methodology.
AI provides you the rational results which is trained through the process of training the the models and machines and therefore it is with the help of machine learning (python, R programming,Xolo)
When we are saying operational research than we are talking about the methodology of analytics. Currently R programming is been used efficiently for analytics.
Reinforcement learning is the domain of ML and AI that is closest to operations research and focuses on dynamical systems. You may want to look at traditional reinforcement learning and also deep reinforcement learning.
Operations research and deep learning both aim at optimization at different perspectives. But the fact that deep learning does something different than algebra is what that makes deep learning different. I feel quantum computing assisted deep learning will change the use of operations research. But generalized AI (mainly driven by deep learning) is far from today's scope. When a deep learning model can be generalized, it can be used for operations research effectively.