Towards Data Science

Understanding the process behind agentic planning and task management in LangChain The post How Agents Plan Tasks with To-Do Lists appeared first on Towards Dat...

A data scientist's guide to population stability index PSI The post Stop Retraining Blindly: Use PSI to Build a Smarter Monitoring Pipeline appeared first on To...

A brief overview of the math behind the Harsanyi Dividend and a real-world application in Streamlit The post Synergy in Clicks: Harsanyi Dividends for E-Commerc...

Understanding text embeddings through simple models and Excel The post The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel appeared first on Towa...

Gradient descent in function space with decision trees The post The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel...

From Random Ensembles to Optimization: Gradient Boosting Explained The post The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in...

For the last couple of years, a lot of the conversation around AI has revolved around a single, deceptively simple question: Which model is the best? But the ne...

A story about failing forward, spheres you can’t visualize, and why sometimes the math knows things before we do The post The Geometry of Laziness: What Angles...

How to make LLMs reason with verifiable, step-by-step logic Part 1 The post Understanding Vibe Proving appeared first on Towards Data Science....

An LLM that's 41× more efficient and 9× faster than today's standard models The post What Happens When You Build an LLM Using Only 1s and 0s appeared first on T...

Comparing metrics across datasets and models The post How to Do Evals on a Bloated RAG Pipeline appeared first on Towards Data Science....

Comparing metrics across datasets and models The post Running Evals on a Bloated RAG Pipeline appeared first on Towards Data Science....

MCP is a key enabler into turning your LLM into an agent by providing it with tools to retrieve real-time information or perform actions. The post Tools for You...

What do regular technology users think and know about AI? The post Understanding the Generative AI User appeared first on Towards Data Science....

Learn how to analyze product performance, extract time-series features, and uncover key seasonal trends in your sales data. The post EDA in Public Part 2: Produ...

Understanding ensemble learning from first principles in Excel The post The Machine Learning “Advent Calendar” Day 19: Bagging in Excel appeared first on Toward...

Using Agentic AI prompts with the Artificial Bee Colony algorithm to enhance unsupervised clustering and optimization workflows. The post Agentic AI Swarm Optim...

From a weekend chore to a fun application of valuable operations research principles The post How I Optimized My Leaf Raking Strategy Using Linear Programming a...

Best practices for data quality, retrieval design, and evaluation in production RAG systems The post Six Lessons Learned Building RAG Systems in Production appe...

'Here is a short, clear excerpt, written in your style and suitable for Medium or Towards Data Science:

With concrete examples of using AI Studio Build mode to learn faster, prototype smarter, communicate clearer, and automate quicker. The post 4 Ways to Superchar...

An optimal solution to the well-known NP-complete problem, when the input values are close enough to each other. The post The Subset Sum Problem Solved in Linea...

Using Python to generate art The post Generating Artwork in Python Inspired by Hirst’s Million-Dollar Spots Painting appeared first on Towards Data Science....

Here's how to detect point anomalies within each series, and identify anomalous signals across the whole bank The post A Practical Toolkit for Time Series Anoma...