AI Agents in Production: What Actually Works (Based on 300+ Deployments)
Author(s): Artem Shelamanov Originally published on Towards AI. As 2025 comes to an end, everyone wants to wrap themselves in cozy blankets, stare at the Christmas tree, and relax with a mug of hot cocoa. Instead, many data scientists are working overtime …
How I Automated Sales KPI Reporting with n8n and Cut 99% of Manual Work
Author(s): Apoorvavenkata Originally published on Towards AI. Every sales organization depends on understanding which distributors perform best and which items drive the most volume. Yet in many analytics teams, this information remains trapped in spreadsheets, requiring manual cleanup, complex formulas, pivot tables, …
How to Craft a Strong AI/ML Thesis Statement
Author(s): Ayo Akinkugbe Originally published on Towards AI. Defining Scope, Hypotheses, and Contribution Boundaries for Clarity, Testability, and Impact in AI & ML Research Photo by Omar:. Lopez-Rincon on Unsplash Snapshot A thesis statement is the central claim of your dissertation or …
Understanding Retrieval in RAG Systems: Why Chunk Size Matters
Author(s): Sarah Lea Originally published on Towards AI. A step-by-step retrieval guide using sentence transformers, chunk size and similarity scores. These are exactly the kinds of answers we expect today from retrieval-augmented generation systems. You upload a PDF, ask a few questions, …
I Tested 12 Quantization Methods: The Winner Surprised Me (2-Bit vs 4-Bit)
Author(s): Manash Pratim Originally published on Towards AI. Small LLM Engineering #7 Everyone says 4-bit quantization is the practical limit. Image generated using AIThis article explores the implications of different quantization methods for machine learning models, particularly focusing on 2-bit and 4-bit …
The AI Engineering Bookshelf: Five Books That Changed How I Think About Building AI Systems
Author(s): Hamza Khaled Mahmoud Originally published on Towards AI. The AI Engineering Bookshelf: Five Books That Changed How I Think About Building AI Systems Few engineers have the luxury of reading every technical book cover-to-cover. I certainly haven’t. But deep engagement with …
What Healthcare Taught Me About Churn (Hint: Classification Is the Wrong Tool)
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. Using survival analysis to predict when customers leave — and avoid a common data leakage trap Most churn models answer the wrong question: They tell you who might leave but not when. Observed …
ChatGPT Is Built With Millions of These (Sort of): Understanding the OG Perceptron
Author(s): Sayan Chowdhury Originally published on Towards AI. Understanding the OG Perceptron Neural networks look complex from the outside, but at their core they are built from one simple unit. This unit is called the perceptron. The OG 😀The article explains the …
Creating an AI-powered Database Assistant with OpenAI, SQLAlchemy, and Conversational Buffer Memory
Author(s): VARUN MISHRA Originally published on Towards AI. Creating an AI-powered Database Assistant with OpenAI, SQLAlchemy, and Conversational Buffer Memory In this tutorial, we will walk through the process of creating a sophisticated AI-powered database assistant that converts natural language queries into …
Unveiling the BLEU Score: Your Guide to Judging Machine Translation Quality
Author(s): VARUN MISHRA Originally published on Towards AI. Unveiling the BLEU Score: Your Guide to Judging Machine Translation Quality Machine translation has come a long way, from clunky rule-based systems to sleek neural models like Transformers. But how do we know if …
AI Papers to Read in 2025
Author(s): Ygor Serpa Originally published on Towards AI. Photo by Susan Q Yin on Unsplash Today, I return to Medium with my series of AI paper recommendations. My long-term followers might recall the four previous editions ([1], [2], [3], and [4]). I’ve …
Linear Transformation vs. Change of Basis (Deep Dive)
Author(s): Irene Markelic, PhD Originally published on Towards AI. Mastering the Math Behind AI, Machine Learning and Data Science Linear transformations and Change of Basis are deceptively simple concepts that tempt us to rush over them quickly. However, mastering the duality between …
Mastering Extractive Summarization: A Theoretical and Practical Guide to TF-IDF and TextRank
Author(s): VARUN MISHRA Originally published on Towards AI. Mastering Extractive Summarization: A Theoretical and Practical Guide to TF-IDF and TextRank Text summarization is a cornerstone of natural language processing (NLP), enabling us to distill lengthy documents into concise summaries. Two popular extractive …
Understanding L1 and L2 Regularization in Machine Learning
Author(s): VARUN MISHRA Originally published on Towards AI. Understanding L1 and L2 Regularization in Machine Learning Regularization is a fundamental technique in machine learning used to prevent overfitting, improve model generalization, and ensure that models perform well on unseen data. Two of …
(p,d,q): The Understated Framework Behind Serious Forecasting
Author(s): VARUN MISHRA Originally published on Towards AI. (p,d,q): The Understated Framework Behind Serious Forecasting Forecasting is often treated as a technological problem — throw data into a model, tweak a few knobs, and wait for predictions to appear. The reality is …
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