Machine Learning Introduction. Class Info Office Hours –Monday:11
Por um escritor misterioso
Descrição
Important Come to class. Pay attention. Ask questions. –There are no stupid questions!! Come to my office hours Start the homework assignments early Homework in this class requires “thinking time” Read the textbook and notes –The textbook can be difficult to read: very technical
1 What algorithms can approximate functions well (and when). How does number of training examples influence accuracy. How does complexity of hypothesis representation impact it. How does noisy data influence accuracy. What are the theoretical limits of learnability. How can prior knowledge of learner help. What clues can we get from biological learning systems. How can systems alter their own representations .
1 What algorithms can approximate functions well (and when). How does number of training examples influence accuracy. How does complexity of hypothesis representation impact it. How does noisy data influence accuracy. What are the theoretical limits of learnability. How can prior knowledge of learner help. What clues can we get from biological learning systems. How can systems alter their own representations .
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por adulto (o preço varia de acordo com o tamanho do grupo)
