假设
In computer science, we stand on the shoulders of giants, but we must also be willing to question their assumptions.
"A key insight in computational learning theory is that the complexity of a learning problem is determined by the complexity of the hypothesis space and the amount of data available."
The complexity of a learning problem is often determined by the size and structure of the hypothesis space.
A key insight in learning theory is that the complexity of a hypothesis class is crucial for generalization.
We must always question our assumptions and be willing to revise our theories in light of new evidence.
There are two possible outcomes: if the result confirms the hypothesis, then you've made a measurement. If the result is contrary to the hypothesis, then you've made a discovery.
There are two possible outcomes: if the result confirms the hypothesis, then you've made a measurement. If the result is contrary to the hypothesis, then you've made a discovery.
"We must constantly challenge our assumptions and be willing to change our minds."
The first erroneous assumption is that quality means goodness, or luxury, or shininess, or weight. Quality means conformance to requirements.
The first erroneous assumption is that quality means goodness, or luxury, or shininess, or weight.
The only way to understand another culture is to assume the frame of reference of that culture.
The only way you can write the truth is to assume that what you set down will never be read.
The only way you can write the truth is to assume that what you set down will never be read.