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MLPills - Year in Review 2025

If we had to summarize 2025 in one sentence, it would be: The year we moved from “Prompts” to “Systems.”

Dec 28, 2025 • David Andrés

Issue #116 - Introduction to Vector Search

For decades, search engines operated on a simple premise: exact matching. If you searched for “car troubleshooting,” the engine looked for documents…

Dec 21, 2025 • David Andrés

Issue #115 - Reranking in your RAG pipeline

If you are building an AI application today, you are likely using RAG (Retrieval-Augmented Generation). It is the standard architecture for giving Large…

Dec 14, 2025 • David Andrés

Issue #114 - The Landscape of Time Series Forecasting

Time series analysis involves examining a sequence of data points collected over time to uncover hidden patterns. By analyzing historical data, we can…

Dec 6, 2025 • David Andrés

Issue #113 - Interpreting XGBoost predictions

Modern machine learning models are often capable of impressive predictive performance, but they are also criticised for being opaque. Understanding not…

Nov 30, 2025 • David Andrés

Most Popular

Issue #88 - Introduction to SHAP values

Jan 29, 2025 • David Andrés and Muhammad Anas

DIY #12 - SHAP in Action: Making ML Explainable

Feb 15, 2025 • David Andrés and Muhammad Anas

Issue #67 - Exploratory Data Analysis

Jul 28, 2024 • David Andrés and Josep Ferrer

RW #3 - EDA applied to Netflix (part I)

Mar 30, 2025 • David Andrés and Muhammad Anas

DIY

DIY #18 - Orchestrator-Worker LLM Agent with LangChain

Imagine you’re managing a complex research project. You need to analyze a company’s financial health, but that requires gathering quarterly reports…

Nov 23, 2025 • David Andrés

DIY #17 - Parallelisation with LangChain

Imagine you’re a news editor trying to understand a breaking story. You get a single field report. To really cover it, you need to know the “who, what…

Nov 1, 2025 • David Andrés

DIY #16 - Build a Persistent Conversational Agent with LangGraph

In this article, we'll build exactly that: a Python-based conversational agent using LangGraph that can remember user information across sessions and…

Sep 7, 2025 • David Andrés

DIY #15 - Prompt Chaining with LangChain

Imagine you have a complex task, like writing a detailed report or analyzing a lengthy customer feedback document. Trying to get an AI to do it all in…

Jun 29, 2025 • David Andrés

DIY #14 - Step-by-step implementation of a ReAct Agent in LangGraph

Large Language Model (LLM) agents can make decisions about when to use external tools as part of answering a question. Let’s now cover the most basic…

Apr 20, 2025 • David Andrés

Real-World

RW #8 - Turning Podcasts Into Knowledge Graphs

Picture this: You’ve just finished listening to a fascinating 2-hour podcast. The expert dropped dozens of insights, research findings, and connections…

Sep 28, 2025 • David Andrés

RW #7 - When to use Rules, ML or LLMs?

Deciding between a simple, rule-based system and a sophisticated machine learning (ML) model is a critical choice in software development. While it's…

Sep 20, 2025 • David Andrés

RW #6 - Text-Moderation System with Embeddings

This week we’re handing you a plug-and-play, notebook-ready tutorial you can drop straight into Jupyter or VS Code. Inside you’ll find:Why an…

Aug 3, 2025 • David Andrés

RW #5 - No-Code Customer Service agent with LangFlow

Imagine a customer service operation where AI agents don't just rely on generic responses, but actually understand the business inside and out. Agents…

Jul 13, 2025 • David Andrés

RW #4 - EDA applied to Netflix (part II)

Welcome back! In Part I, we laid the groundwork for exploring Netflix’s data—distributions, ratings, and top producing countries. Now, in Part II, we’re…

Apr 13, 2025 • Muhammad Anas and David Andrés

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