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Alex Molas Blog

alexmolas.com

Hello, world, I'm Alex, and this is my blog, where I talk about math, machine learning, and other things like cooking.

MathAI / MLPythonEssays / personal

’20’21’22’23’24’25’26
Posts
65 from 31 Dec 2020 to 23 Sep 2026
Posting
now and then (1 in the last year)
Kind
personal blog
Feed
https://www.alexmolas.com/feed.xml

2026 1

  1. Jev can’t be calibrated

2025 6

  1. Bayesian A/B testing is not immune to peeking
  2. Adding search to my static blog.
  3. Who needs git when you have 1M context windows?
  4. Semantic Unit Testing
  5. Three symmetric math riddles
  6. Optimizing Jupyter Notebooks for LLMs

2024 10

  1. Win your fantasy league using operations research
  2. Something happens to everyone.
  3. In defense of Leetcode Interviews
  4. Good code is rarely read
  5. You need more than p-values
  6. hn-index
  7. A search engine in 80 lines of Python
  8. ChatGPT knows things that Google doesn’t
  9. Guide to onboarding in a new job
  10. 2023 review

2023 25

  1. I hate MFA
  2. Conditioning is grouping by
  3. The least controversial movie
  4. Reading S3 data from local PySpark
  5. Stupid by choice
  6. Different Types of Means
  7. How far can you jump from a swing?
  8. Analyzing Gender Gap in Chess
  9. Expected $k$ highest value from $n$ Gaussian draws.
  10. Good Science, Good Engineering.
  11. You’re the best at something.
  12. 512KB Club
  13. Automate your static blogroll.
  14. About math limitations.
  15. Nobody cares about your blog.
  16. Why did I make my blog uglier?
  17. A game for the next 15 years: counting license plates
  18. How much for your brain?
  19. Debunking the Myth of Dollar Cost Averaging
  20. A randomized voting strategy
  21. How to initialize your bias.
  22. The error of the error.
  23. The Sweet Spot for Buying Used Cars.
  24. Discovering the best Chess960 variation.
  25. 2022 review

2022 22

  1. Can Random Forests overfit?
  2. Mate with only pawns and no promotions.
  3. Computability Theory (ii): uncomputable numbers.
  4. Computability Theory (i): the Halting Problem.
  5. Choose the smallest number not chosen yet.
  6. TIL: constant folding in python.
  7. L1 regularization from a bayesian perspective
  8. Field theory for recurrent mobility
  9. Your laptop is an implementation detail
  10. Vectorizing impossible operations: boolean algebra, sets, and filters
  11. Data science preflight checklist.
  12. Why do we minimize the mean squared error?
  13. Training TensorFlow models with big tabular datasets (iii): preparing a warmup for TensorFlow models.
  14. Why bureaucracy is fundamentally wrong.
  15. Feynman’s Restaurant Problem.
  16. Counterintuitive statistics (i): a fair coin game.
  17. Training TensorFlow models with big tabular datasets (ii)
  18. Coding sucks.
  19. Training TensorFlow models with big tabular datasets (i).
  20. Continuous Blackjack (ii): deriving basic equations from two other perspectives.
  21. Continuous Blackjack (i): introduction and first results.
  22. Data Science and Software Engineering (I)

2020 1

  1. Dynamic Programming (i): Multiplying Matrices