Mathematical Optimization (DL, ML)

In this personal note, I would like to discuss the field of mathematical optimization, which is closely related to Deep Learning and Machine Learning. Mathematical optimization is a branch of mathematics that deals with finding the best solution to a given problem. It involves formulating the problem as a mathematical model and then applying various optimization techniques to find the optimal solution.

AI is a broad field that encompasses various subfields, including Deep Learning and Machine Learning. Deep Learning is a subset of Machine Learning that focuses on training artificial neural networks with multiple layers to learn and make predictions. It has been widely used in various applications, such as image recognition, natural language processing, and speech recognition.

Machine Learning is a branch of AI that focuses on developing algorithms and models that can learn from data and make predictions or decisions without being explicitly programmed. It involves training a model on a dataset and then using that model to make predictions or decisions on new, unseen data.

Overall, the fields of Deep Learning and Machine Learning are integral parts of the broader field of AI. They have revolutionized many industries and continue to advance our understanding of artificial intelligence.