Helpful Websites/Blogs

Here is a list of websites and blogs that I find helpful for learning about different topics in Computer Science.

The Morning Paper


The Morning Paper: a short summary every weekday of an important, influential, topical or otherwise interesting paper in the field of computer science.

A good way to keep up with what’s going on in various research areas in Computer Science.


Metacademy is built around an interconnected web of concepts, each one annotated with a short description, a set of learning goals, a (very rough) time estimate, and pointers to learning resources. The concepts are arranged in a prerequisite graph, which is used to generate a learning plan for a concept. Here are the learning plan and graph for deep belief nets.

It is a good place to quickly learn about a specific topic without the need to go through a whole textbook. Currently, the website focuses more on topics related to machine learning and artificial intelligence.


Principles of Data Reduction

Key Definitions:

  • The Sufficiency Principle: sufficient statistics, ancillary statistics

T is a sufficient statistic of x if T contains all the information that is needed to estimate the parameter \theta. 

  • The Likelihood Principle

The likelihood function L(\theta | x) is a sufficient statistic (controversial)

  • The Equivariance Principle


Properties of a Random Sample

Key Definitions:

independent and identically distributed random variables (i.i.d.)

sampling from an infinite population, sampling from a finite population (with replacement, without replacement)

sampling distribution (the distribution of a statistic)

order statistics #Def. 5.4.1 p.226

weak law of large numbers (WLLN) #Theorem 5.5.2 p.232

strong law of large numbers #Theorem 5.5.2 p.235

OSI 7 Layers

Layer 1: Physical Layer (Ethernet)

Layer 2: Data Link Layer

Layer 3: Network Layer (IP)

Layer 4: Transport Layer (TCP, UDP)

Layer 5: Session Layer (RPC)

Layer 6: Presentation Layer (encryption)

Layer 7: Application Layer (HTTP, FTP)