This is the start of Stanford’s Machine Learning instructing by Andrew Ng. Andrew Ng is the director of Stanford AI lab and the cofounder of Coursera where I will be getting the course resources. Notes is not provided in Coursera version of the course, but it can be found at Stanford’s website. Introduction Machine learning grew out … Continue reading Stanford ML Week 1: Linear Regression with One Variable
Finally, I have reached the end of CS50x, this week we did our final project. There are many projects on display here. The projects are divided into several categories. You can use any skills your learnt in CS50x to aid in making your final project. Students are also encouraged to buy a domain for their final project. … Continue reading CS50x Week 12: Final Project!
While reading Scott Aaronson’s blog here, I was introduced to a book called The Golden Ticket: P, NP, and the Search for the Impossible by Lance Fortnow. It is a book explaining the most important question in Computer science and Mathematics, is P = NP? Alternatively, you can watch Scott Aaronson talk about P = … Continue reading Book review: The Golden Ticket: P, NP, and The Search For The Impossible
Efficiency How much time it takes for our program to run.
def linearSearch(L, x):
for e in L:
if e == x:
The function iterates elements in list L, if the element is equals to x, it returns true. This function continues to iterate until x is found, or if not found, returns false. There are two extreme cases here, if x happens to be … Continue reading 6.00.1x Week 5 (Incomplete)