[K-MOOC] Instruction to Deep Learning: 1-1. Outline of machine learning

Definition of Artificial Intelligence

1. the state that machine has intelligence (Nils Nilsson, 2010, 'The quest of AL')
2. but the problem is that the intelligence is ambiguous
   

Practical Definition of AI

1. the technology that machine could carry out a process in smart way
2. whole range of research of AI scientist (Stanford AI 100 years Report)
3. the complex of all elements of recognition process in human being
   

History of AI

1. 1956s: 
1. a first use of the term, 'Artificial Intelligence', 
2. meaning of 'to proceed on the basis of the conjecture that every of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it' (on Dartmouth College Workshop)
   
   
   
2. 1970s, 1990s: First AI winter, even though huge amount of investments and financial supports is gathered, the outcome was none and all those supports were cut off
   
3. 2010s: the interest and expectation to AI is growing
   
   

Relationship of AI, ML, DL

Definition of Machine Learning

1. the completely different method from the conventional programming method
1. programming method: data → program → output
2. Machine learning: data & output → algorithm → program
2. a detailed field of AI that functions intellectually after a computer is learning from its experience
3. in mathematical meaning,
1. y = h(x)
   y: output
   h: function
   x: feature
2. is finding the function h, h( ), which is the closest to target function by using a set of sample, S={(x, y)}
   

What is the Deep Learning?

1. a multilayered structure of Neural Networks (large scale)
2. is being trained by hierarchical abstract learning

Benefits of DL

1. End-to-End learning: just give input data and get output