SPP-Net Paper Walkthrough: Breaking the Fixed-Size Constraint
Learn how Spatial Pyramid Pooling enables CNNs to handle any image size, with a from-scratch PyTorch implementation
The post SPP-Net Paper Walkthrough: Breaking the Fixed-Size Constraint appeared first on Towards Data Science.
How to Implement Structured Output with Local LLMs
Why use it? How to implement it? What can we do when it fails?
The post How to Implement Structured Output with Local LLMs appeared first on Towards Data Science.
Before Q, K, and V: Reconstructing the Transformer
Many Transformer explainers start with the finished architecture. We ask why it looks the way it does.
The post Before Q, K, and V: Reconstructing the Transformer appeared first on Towards Data Science.
Matplotlib vs Plotly: Which Python Chart Tool Should You Choose?
From Static Plots to Interactive Data Exploration
The post Matplotlib vs Plotly: Which Python Chart Tool Should You Choose? appeared first on Towards Data Science.
Loop Engineering for Listing Questions: When the Answer Is Every Passage, Not the Top One
Enterprise Document Intelligence [Vol.1 #12] - The category of question most RAG pipelines silently fail on, and the pipeline shape that handles them
The post Loop Engineering for Listing Questions: When the Answer Is Every Passage, Not the Top One appeared first on Towards Data Science.
The Problem with pandas Isn’t Performance. It’s Cognitive Overhead.
Faster dataframe engines are nice, but they don't reduce the amount of syntax an analyst has to hold in their head.
The post The Problem with pandas Isn’t Performance. It’s Cognitive Overhead. appeared first on Towards Data Science.
Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer
Enterprise Document Intelligence [Vol.1 #11] - When the first answer points elsewhere in the document, the pipeline loops back to fetch the linked context
The post Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer appeared first on Towards Data Sc...
How a Frontier Model Gets Built, Read from the Kimi K3 Report
An open, 2.8-trillion-parameter model shipped with 47 pages of its own recipe. Reading it tells you what building a frontier model now involves, and how little of it is the model.
The post How a Frontier Model Gets Built, Read from the Kimi K3 Report appeared first on Towards Data Science.
A primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of using unlabelled data.
The post Introduction to Semi-Supervised Learning appeared first on Towards Data Science.
How to Get More Statistical Power from Fewer Research Participants
An online simulation and a novel method for increasing power
The post How to Get More Statistical Power from Fewer Research Participants appeared first on Towards Data Science.
Create a local CLI Agent from scratch completely for free
The post How to Build CLI Agents with Python & Ollama appeared first on Towards Data Science.
The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain?
What actually makes a Forward Deployed Engineer, told through one supply chain project.
The post The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain? appeared first on Towards Data Science.
When the Code Becomes the CEO: Why Your Next Manager Might Be a Decentralized Agentic Loop
In five to ten years, the sharpest manager in your company might not be human, might not sleep, and might exist entirely in shared GPU memory. This is the systems-level view of the algorithmic corporation — why middle management collapses into a protocol, what breaks in the current AI stack, and wha...
How to Debug AI Coding Agents When They Change the Wrong Thing
A practical tutorial for recording model tool requests, real function results, patches, checks, screenshots, and a saved run log.
The post How to Debug AI Coding Agents When They Change the Wrong Thing appeared first on Towards Data Science.
How Benders Decomposition Works Part I: Optimality Cuts
A friendly introduction to one of the most powerfull optimization techniques using the uncapacitated facility location problem
The post How Benders Decomposition Works Part I: Optimality Cuts appeared first on Towards Data Science.
How one open-source ecosystem made state-of-the-art AI accessible
The post The Python Ecosystem That Changed AI Development appeared first on Towards Data Science.
What it actually takes to turn a company's scattered knowledge into something an LLM can reliably use — and why the demo is 5% of the work.
The post How to Build a Context Layer and a Company Brain appeared first on Towards Data Science.
The full conjecture is stated over abstract fields, but the counterexample is a concrete 3D function that we can explain and visualize using familiar geometric ideas and a little algebra.
The post A Simplified View of the Jacobian Conjecture appeared first on Towards Data Science.
How statistical physics explains the transition from deterministic predictions to generative AI.
The post How to Decode the Temperature Parameter in LLMs appeared first on Towards Data Science.
Why Your Best Predictive Model Gives the Wrong Treatment Effect
Why prediction-driven variable selection misses confounders and how Bayesian Adjustment for Confounding attempts to fix it.
The post Why Your Best Predictive Model Gives the Wrong Treatment Effect appeared first on Towards Data Science.