Technical Fridays | Blog
Personal notes on machine learning, deep learning, and software engineering — what's Technical Fridays?
- Personal
- Data Science
- Machine Learning
- R
- Python
- Algorithms
- Cryptography
- Mathematics
- Visualization
- Deep Learning
- Computer Vision
- Natural Language Processing
- Generative AI
- Speech Recognition
- PyTorch
- LLM
- CUDA
- Agentic AI
-
MathematicsMathematics and Beauty
A reflection on the aesthetic beauty found in mathematics from elegant proofs to surprising results like the parity of zero.
-
CryptographyHow secure are we?
An overview of online security, explaining how HTTPS, SSL/TLS, and encryption protect communications on the web.
-
AlgorithmsStructure of the web
Exploring the bowtie structure of the web, how directed graph analysis reveals the web's giant strongly connected component and its IN/OUT regions.
-
Data ScienceSimpson's paradox
Simpson's paradox explained through UC Berkeley's 1973 admissions data, a trend that reverses when data is aggregated across groups.
-
Data ScienceEmail spam filtering: Text analysis in R
Building and evaluating an email spam filter using text analytics and machine learning in R.
-
Data ScienceFriendship paradox: facebook
Exploring the friendship paradox, phenomenon where most people have fewer friends than their friends have on average, using Facebook data and Python.
-
Python
Turtle in Python: A Traffic light
A step-by-step guide to simulating a traffic light using Python's turtle graphics module with timed state transitions.
-
Data ScienceMoneyball: Why no prediction can't be made for baseball champion
Using logistic regression in R to explore why ML cannot reliably predict the baseball World Series champion.
-
Data ScienceMoneyball: How linear regression changed baseball
How Oakland A's used linear regression in R to identify undervalued players and compete despite limited budget.
-
PersonalTechnical Fridays
Introducing Technical Fridays, a weekly technical writing series covering topics from data science to algorithms.