The purpose of this documentation is to record all the findings and my progress while exploring Firefox source code, in order to log how many time a DOM API is called when visit a single website, or multiple common website.
This require a deep modification in Firefox’s implementation of DOM API.
Week 3 of professor Andrew Ng’s Machine Learning course on Coursera.
Nếu bạn có dư dả thời gian và nguồn kinh phí eo hẹp, thì cách tốt nhất để dạo vòng quanh các nước EU chính là các phương tiện công cộng.
In this blog, I will instruct you on how to install and writing LaTex documents on Windows with ease.
This post gives the solutions and the detailed reasoning for each exercise in week 2 of professor Andrew Ng’s Machine Learning course.
See the other posts at Machine Learning Course Structure.
Week 2, part 2 of professor Andrew Ng’s Machine Learning course. In this post we’ll look at an alternative to the Gradient Descent algorithm along with its pros and cons.
Week 2 of professor Andrew Ng’s Machine Learning course on Coursera. In this part you’ll see linear regression extended to multiple input features, along with the best practices for doing linear regression.
The 4th post in the series on self-studying professor Andrew Ng’s Machine Learning course on Coursera.
In this post we’ll talk about Matrices and Vectors, along with their operations.
The 3rd post in the self-study Machine Learning series.
In the previous 2 posts we got the hypothesis function and a way to tell whether that function fits our set of training examples. Now we’ll find a way to determine the parameters for the hypothesis function.
The 2nd post in the self-study Machine Learning series. In this post we’ll look at the cost function, a function for predicting the output value given a set of input/output values.