You can see the one-paragraph description of the blog in the footers, repeated here for convenience:
This is my blog, where I have written over 225 articles on a variety of topics, most of which are about one of two major themes. The first is computer science, which is my area of specialty as a Ph.D. student at UC Berkeley. The second can be broadly categorized as “deafness,” which relates to my experience and knowledge of being deaf.
The easiest way to find something that you’ll be interested in is to look at the archives and browse the titles, which (I hope) are descriptive. Using the built-in Google site search there would also be useful.
If you’re interested in knowing more about the classes at Berkeley, I write reviews on all the ones I have taken. Here are a few examples:
- CS 287, Advanced Robotics
- CS 288, Natural Language Processing
- CS 294-112, Deep Reinforcement Learning
- CS 294-115, Algorithmic Human-Robot Interaction
- EE 227BT, Convex Optimization
- EE 227C, Convex Optimization and Approximation
- STAT 210A, Theoretical Statistics
When I was preparing for the AI prelims at Berkeley, I wrote a lot about AI topics. I also wrote a “transcript” of my prelims.
- My Prelims [Transcript]
- Markov Decision Processes and Reinforcement Learning
- Perceptrons, SVMs, and Kernel Methods
- Notes on Exact Inference in Graphical Models
- The Least Mean Squares Algorithm
- Hidden Markov Models and Particle Filtering
I also write a lot about other technical areas, and am attempting to write up more about my thoughts on various technical research papers. Here are a few:
- Going Deeper Into Reinforcement Learning: Fundamentals of Policy Gradients
- Going Deeper Into Reinforcement Learning: Understanding Deep-Q-Networks
- Going Deeper Into Reinforcement Learning: Understanding Q-Learning and Linear Function Approximation
- Understanding Higher Order Local Gradient Computation for Backpropagation in Deep Neural Networks
- Some Recent Results on Minibatch Markov Chain Monte Carlo Methods
- Independent Component Analysis — A Gentle Introduction
- Ten Things Python Programmers Should Know
If you are interested in knowing about what it’s like being deaf, then there are a lot of options. Here are a few that might be informative:
- The Obligatory “Can I Lip Read?” Question
- The BVLC (BAIR) Retreat: Disaster Averted!
- Advocate for Yourself
- After a Few Weeks of CART, Why do I Feel Dissatisfied?
- The Problem with Seminars
- My Pre-College Education as a Deaf Mainstreamed Student
- New Closed-Captioning Glasses
- Hearing Aids: How They Help and How They Fall Short in Group Situations
- Technical Term Dilemma
- Why Computer Science is a Good Major for Deaf Students
Finally, I write sometimes about the books I read, such as in the following: