Work in progress: 181,232 of 181,233 sites checked so far, more every week · updated 2 Nov 2026Missing a blog? Tell us

Top all-time · #9178

R

Rahul Agarwal

Personal blog · mlwhiz.comdataaicareer

Rahul Agarwal writes MLWhiz: Recs|ML|GenAI, a personal blog at mlwhiz.com about data, ai and career. Since 2016, 8 different Hacker News readers have linked it 84 times, most often “Don't Trust Everything That Goes on the Kaggle Discussion Forums”. It is still writing: the last post was on 2026-10-17, and you can follow it by feed.

Visit the blog
84mentions?
8HN people?
2016–2025first – last linked?
Links on Hacker News per year · peak 72 in 2019

Too few sampled comments (1) to say how often HN recommends it.?

Why HN links it

Linked as a explainer on MCMC (Markov chain Monte Carlo) algorithms, with a worked example involving the Beta distribution. The one commenter points to it for anyone unsure what MCMC is.

Summarised by Claude from a sample of 1 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Making ML careers accessible and GenAI, Recsys, and MLOps understandable. 🔧 No-fluff guides and real-world insights to help you build, deploy, and advance in the machine learning and Generative AI ecosystem. with tens of t

Most-linked posts?

  1. Don't Trust Everything That Goes on the Kaggle Discussion Forums
    3 people · 5 mentions · first linked 2019-02-19
  2. Understanding Big Data the Programmer Way
    3 people · 5 mentions · first linked 2019-07-07
  3. The Hitchhiker’s Guide to Feature Extraction
    3 people · 3 mentions · first linked 2019-05-19
  4. Easy Introduction to GANs
    2 people · 5 mentions · first linked 2019-06-17
  5. Transfer Learning for Text Explained – Too Simple
    2 people · 5 mentions · first linked 2019-03-30
  6. Some Great Additions for Your Jupyter Notebooks
    2 people · 4 mentions · first linked 2019-06-28
  7. Creating Baseline is important for your NLP models. Here are some ways
    2 people · 4 mentions · first linked 2019-02-09
  8. NLP Learning Series: Attention, CNN and what not for text classification
    2 people · 4 mentions · first linked 2019-03-09
  9. Learn NLP using this series I wrote in 4 months
    2 people · 2 mentions · first linked 2019-04-21

What Hacker News says?

  1. I believe they are using mcmcs at the core. markov chain multi carlos. this might be useful if you are wondering what it is http://mlwhiz.com/blog/2015/08/19/MCMC_Algorithms_Beta_Distr...

    Comment linking /blog/2015/08/19/MCMC_Algorithms_Beta_Distribution/

    on “Data diversity: Preserving variety in data sets should aid machine learning”
  2. Submitted What Kagglers Are Using for Text Classification as a story · 203 points

    HN discussion
  3. Submitted Visualization techniques for different data sets as a story · 113 points

    HN discussion
  4. Submitted Connected Components – The one Graph Algorithm you need to know as a story · 113 points

    HN discussion
  5. Submitted Object Detection: An End-to-End Theoretical Perspective as a story · 62 points

    HN discussion
  6. Submitted Text Preprocessing Methods for Deep Learning as a story · 50 points

    HN discussion
  7. Submitted Chatbots aren't as difficult to make as you think as a story · 38 points

    HN discussion
  8. Submitted NLP Learning Series: Attention, CNN and what not for text classification as a story · 18 points

    HN discussion
  9. Submitted Chatbots aren't as difficult to make as You Think as a story · 6 points

    HN discussion
  10. Submitted The Complete Guide to PyTorch for Data Scientists as a story · 4 points

    HN discussion
  11. Submitted Transfer Learning for Text Explained – Too Simple as a story · 4 points

    HN discussion
  12. Submitted Explained Transfer Learning in NLP as a story · 4 points

    HN discussion
  13. Submitted Don't Trust Everything That Goes on the Kaggle Discussion Forums as a story · 4 points

    HN discussion
  14. Submitted Top Data Science Resources on the Internet as a story · 4 points

    HN discussion
  15. Submitted Using XGBoost for time series prediction tasks as a story · 4 points

    HN discussion
  16. Submitted How to Move from Keras to Pytorch – Answer as a story · 4 points

    HN discussion
  17. Submitted Create Graphs with SeaBorn- the Most Awesome Python Library for Visualization as a story · 4 points

    HN discussion
  18. Submitted A Layman Guide to Moving from Keras to Pytorch as a story · 4 points

    HN discussion
  19. Submitted How to crack FAANG coding interviews as a story · 3 points

    HN discussion
  20. Submitted BayesianBayesian Bandits as a story · 3 points

    HN discussion
  21. Submitted Minimally Sufficient Pandas for Programmers as a story · 3 points

    HN discussion
  22. Submitted Understanding Big Data the Programmer Way as a story · 3 points

    HN discussion
  23. Submitted Minimal Pandas Subset for Data Scientists as a story · 3 points

    HN discussion
  24. Submitted Some Great Additions for Your Jupyter Notebooks as a story · 3 points

    HN discussion
  25. Submitted Easy Introduction to GANs as a story · 3 points

    HN discussion
  26. Submitted Transfer Learning for Text Classification as a story · 3 points

    HN discussion
  27. Submitted Attention, CNN and What Not for Text Classification as a story · 3 points

    HN discussion
  28. Submitted What My First Medal Taught Me about Kaggle as a story · 3 points

    HN discussion
  29. Submitted What My Silver Medal Taught Me about Text Classification and Kaggle in General? as a story · 3 points

    HN discussion
  30. Submitted Creating Baseline is important for your NLP models. Here are some ways as a story · 3 points

    HN discussion

Search all of HN for mlwhiz.com