Introduction I’ve been taking the Machine Learning course by Dr. Andrew Ng online through Coursera, and so far it’s been an enlightening and enjoyable experience. While I’ve been taking lots of notes on the equations and implementation details on linear and logistic regression models, I thought it would be a fun weekend exercise to implement these algorithms from scratch using my favorite toolkit: Python, Pandas, and Numpy. Special thanks to Dr.
Introduction Mobile trivia apps, such as HQ Trivia and The Q, modernize game show-style entertainment, allowing anyone to try their hand at winning cash prizes from their smartphone from anywhere. However, these applications are susceptible to cheaters and bots. For example, a developer by the name of Toby Mellor recently demonstrated how he created a near-realtime system to cheat on HQ Trivia. His post (linked above) details his use of Google cloud APIs to create this system.
Today, we’re going to do some splunking within the deep, dark place which is your browser history. In order to obtain the data for this tutorial from Google Chrome, go to ~/Library/Application Support/Google/Chrome/Default on a Mac/Linux computer or %LocalAppData%\Google\Chrome\User Data\Default on a Windows PC. Run the following SQLite command to obtain a text file in reverse chronological order: (Mac/Linux) sqlite3 History "select datetime(last_visit_time/1000000-11644473600,'unixepoch'),url from urls order by last_visit_time desc" > ~/hist.
Hello. I am AppleCrazy, and I’m a high school student from the Bay Area who likes to explore and tinker with code. I’ve completed a few projects, and am doing a few more right now. This is a place for me to share interesting things, publish project postmortems, and do some general reflection of the general state of things, and I hope it’s a useful resource for others. At the time of this writing, this blog is using the Hugo static site generator.