The Arithmetic of Productivity Boosts: Why Does a “40% Increase in Productivity” Never Actually Work?
Why do grand productivity promises never actually deliver? Is every product just bad, or is there something else hiding in the numbers? The post The Arithmetic of Productivity Boosts: Why Does a “40% Increase in Productivity” Never Actually Work? appeared first on Towards Data Science.
Context Engineering for AI Agents: A Deep Dive
How to optimize context, a precious finite resource for AI agents The post Context Engineering for AI Agents: A Deep Dive appeared first on Towards Data Science.
From 4 Weeks to 45 Minutes: Designing a Document Extraction System for 4,700+ PDFs
How a hybrid PyMuPDF + GPT-4 Vision pipeline replaced £8,000 in manual engineering effort, and why the latest models weren’t the answer The post From 4 Weeks to 45 Minutes: Designing a Document Extraction System for 4,700+ PDFs appeared first on Towards Data Science.
Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI
A practical system design combining open-source Bayesian MMM and GenAI for transparent, vendor independent marketing analytics insights. The post Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI appeared first on Towards Data Science.
Grounding Your LLM: A Practical Guide to RAG for Enterprise Knowledge Bases
A clear mental model and a practical foundation you can build on The post Grounding Your LLM: A Practical Guide to RAG for Enterprise Knowledge Bases appeared first on Towards Data Science.
How to Use Claude Code to Build a Minimum Viable Product
Learn how to effectively present product ideas by building MVPs with coding agents The post How to Use Claude Code to Build a Minimum Viable Product appeared first on Towards Data Science.
Detecting Translation Hallucinations with Attention Misalignment
A low-budget way to get token-level uncertainty estimation for neural machine translations The post Detecting Translation Hallucinations with Attention Misalignment appeared first on Towards Data Science.
How to Run Claude Code Agents in Parallel
Learn how to apply coding agents in parallel to work more efficiently The post How to Run Claude Code Agents in Parallel appeared first on Towards Data Science.
The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition
The geometric foundations you need to understand the dot product The post The Geometry Behind the Dot Product: Unit Vectors, Projections, and Intuition appeared first on Towards Data Science.
Behavior is the New Credential
We are living through a paradigm shift in how we prove we are who we say we are online. Instead of asking What do you know? (password, PIN, mother’s maiden name) or What do you look like? (Face ID, fingerprint) the question has become How do you behave? The post Behavior is the New Credential appear
Building Robust Credit Scoring Models with Python
A Practical Guide to Measuring Relationships between Variables for Feature Selection in a Credit Scoring. The post Building Robust Credit Scoring Models with Python appeared first on Towards Data Science.
Building a Python Workflow That Catches Bugs Before Production
Using modern tooling to identify defects earlier in the software lifecycle. The post Building a Python Workflow That Catches Bugs Before Production appeared first on Towards Data Science.
A Data Scientist’s Take on the $599 MacBook Neo
Why it doesn’t fit my workflow but still makes sense for beginners The post A Data Scientist’s Take on the $599 MacBook Neo appeared first on Towards Data Science.
Proxy-Pointer RAG: Achieving Vectorless Accuracy at Vector RAG Scale and Cost
A new way to build vector RAG—structure-aware and reasoning-capable The post Proxy-Pointer RAG: Achieving Vectorless Accuracy at Vector RAG Scale and Cost appeared first on Towards Data Science.
I Replaced Vector DBs with Google’s Memory Agent Pattern for my notes in Obsidian
Persistent AI memory without embeddings, Pinecone, or a PhD in similarity search. The post I Replaced Vector DBs with Google’s Memory Agent Pattern for my notes in Obsidian appeared first on Towards Data Science.
DenseNet Paper Walkthrough: All Connected
When we try to train a very deep neural network model, one issue that we might encounter is the vanishing gradient problem. This is essentially a problem where the weight update of a model during training slows down or even stops, hence causing the model not to improve. When a network is very deep,
Quantum Simulations with Python
Run Quantum Experiments with Qiskit-Aer The post Quantum Simulations with Python appeared first on Towards Data Science.
How to Handle Classical Data in Quantum Models
Workflows and encoding techniques in quantum machine learning The post How to Handle Classical Data in Quantum Models appeared first on Towards Data Science.
Linear Regression Is Actually a Projection Problem (Part 2: From Projections to Predictions)
The Vector View of Least Squares. The post Linear Regression Is Actually a Projection Problem (Part 2: From Projections to Predictions) appeared first on Towards Data Science.
What Happens Now That AI is the First Analyst On Your Team?
How I am adapting in my career in the age of AI, automation, and when everything moving faster than expected. The post What Happens Now That AI is the First Analyst On Your Team? appeared first on Towards Data Science.