I take notes when I learn something new. Here, I share some of them below. These notes have more details than my posts.
- Probabilistic Latent Semantic Analysis with EM algorithm
- Expectation-Maximization Algorithm [PDF] (Update: Feb, 2012)
- Community Detection with Modularity Optimization [PDF]
- Logistic Regression [PDF]
Two Forms of Logistic Regression [PDF]
- Linear Regression [PDF]
- Language Models [PDF]
Although I’m not pursuing a academic career for the moment, it still means a lot for me as Ph.Ds are essentially trained for it. Here, I list several useful and insightful blog posts and articles related to academic career.
Job markt/job hunting:
- Matt Welsh‘s blog series about getting a faculty job is just amazing:
[How to get a faculty job, Part 1: The application]
[How to get a faculty job, part 1b: How to get an interview]
[How to get a faculty job, Part 2: The interview]
[How to get a faculty job, Part 3: Negotiating the offer]
- Ariel Procaccia‘s Tips on job market interviews
The choice/difference between a academic job and an industrial career:
- Matt Welsh left his tenured position in Harvard CS department and join Google for a software engineer position. Want to know why?
[Why I’m leaving Harvard]
- Phillip Guo‘s The Ph.D. Grind should be a must-read for CS Ph.Ds and for the ones are applying graduate schools. Highly recommended.
- David Andersen‘s On the Ph.D.
How to write papers/improve papers