Towards Data Science

2 min read Original article ↗

  • A prerequisite for long-term success of machine learning systems

  • The unconventional career paths you need to explore

Latest

  • What happens when your clear dashboard meets stakeholders who want everything on one screen

  • Exploratory Data Analysis with Pandas

    How to build, score, and interpret RFM segments step by step

  • Robot friends collaborate to learn to fly a drone

  • Image generated by the author with DALL-E 3

    From simple chat to multi-agent reasoning and real-time REST APIs

  • Five key learnings that I discovered during a programming challenge and how they apply to…

  • Understanding retrieval in RAG systems by experimenting with different chunk sizes

  • Gradient Descent, Momentum, RMSProp, and Adam all aim for the same minimum. They do not…

  • With some hints for good numerics

  • AUC measures how well a model ranks positives above negatives, independent of any chosen threshold.

Editor’s Picks

  • Understanding the architecture, training pipeline and implementing TabPFN in practice

  • A hands-on tour of using cProfile + SnakeViz to find (and fix) the “hot” paths…

  • An intuitive explanation of transforming random variables correctly.

  • Illustration comparing MAP and MRR rankings with NDCG and ERR rankings, showing how position-aware metrics reorder items based on graded relevance rather than only the first relevant result.

    MAP and MRR look intuitive, but they quietly break ranking evaluation. Here’s why these metrics…

  • Multiple hypothesis testing, P-values, and Monte Carlo

  • How to make LLMs reason with verifiable, step-by-step logic (Part 1)

  • Comparing metrics across datasets and models

  • Photo by Vardan Papikyan on Unsplash

    What do regular technology users think (and know) about AI?

  • From a weekend chore to a fun application of valuable operations research principles

The Variable Newsletter

  • Don’t miss our most popular articles of the past year!

  • Gain new insights into the art of optimizing your data science and ML workflows

Deep Dives

  • Towards understanding if your agentic solution is actually better

  • A step-by-step guide from weather API ETL to dashboard on Databricks

  • An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into…

  • Understanding the process behind agentic planning and task management in LangChain

  • A brief overview of the math behind the Harsanyi Dividend and a real-world application in…

  • From Random Ensembles to Optimization: Gradient Boosting Explained