How I used n8n to build AI study partners for learning Mandarin: vocabulary, listening, and pronunciation correction.
The post How AI Can Become Your Personal Language Tutor appeared first on Towards Data Science.
Optimizing Data Transfer in Batched AI/ML Inference Workloads
A deep dive on data transfer bottlenecks, their identification, and their resolution with the help of NVIDIA Nsight™ Systems - part 2
The post Optimizing Data Transfer in Batched AI/ML Inference Workloads appeared first on Towards Data Science.
Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example
Walkthrough using open-source prompt optimization algorithms in Python to improve the accuracy of an autonomous vehicle car safety agent running on OpenAI's GPT 5.2
The post Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example appeared first on Towards Data Science....
Federated Learning, Part 1: The Basics of Training Models Where the Data Lives
Understanding the foundations of federated learning
The post Federated Learning, Part 1: The Basics of Training Models Where the Data Lives appeared first on Towards Data Science.
Beyond the Flat Table: Building an Enterprise-Grade Financial Model in Power BI
A step-by-step journey through data transformation, star schema modeling, and DAX variance analysis with lessons learned along the way.
The post Beyond the Flat Table: Building an Enterprise-Grade Financial Model in Power BI appeared first on Towards Data Science.
Beyond Prompting: The Power of Context Engineering
Using ACE to create self-improving LLM workflows and structured playbooks
The post Beyond Prompting: The Power of Context Engineering appeared first on Towards Data Science.
Retrieval for Time-Series: How Looking Back Improves Forecasts
Why Retrieval Helps in Time Series Forecasting We all know how it goes: Time-series data is tricky. Traditional forecasting models are unprepared for incidents like sudden market crashes, black swan events, or rare weather patterns. Even large fancy models like Chronos sometimes struggle because the...
Faster Is Not Always Better: Choosing the Right PostgreSQL Insert Strategy in Python (+Benchmarks)
PostgreSQL is fast. Whether your Python code can or should keep up depends on context. This article compares and benchmarks various insert strategies, focusing not on micro-benchmarks but on trade-offs between safety, abstraction, and throughput — and choosing the right tool for the job.
The post Fa...
I Evaluated Half a Million Credit Records with Federated Learning. Here’s What I Found
Why privacy breaks fairness at small scale—and how collaboration fixes both without sharing a single record
The post I Evaluated Half a Million Credit Records with Federated Learning. Here’s What I Found appeared first on Towards Data Science.
Probabilistic Multi-Variant Reasoning: Turning Fluent LLM Answers Into Weighted Options
Human-guided AI collaboration
The post Probabilistic Multi-Variant Reasoning: Turning Fluent LLM Answers Into Weighted Options appeared first on Towards Data Science.
A practical guide to observability, evaluations, and model comparisons
The post Measuring What Matters with NeMo Agent Toolkit appeared first on Towards Data Science.
Stop Blaming the Data: A Better Way to Handle Covariance Shift
Instead of using shift as an excuse for poor performance, use Inverse Probability Weighting to estimate how your model should perform in the new environment
The post Stop Blaming the Data: A Better Way to Handle Covariance Shift appeared first on Towards Data Science.
A deep dive on data transfer bottlenecks, their identification, and their resolution with the help of NVIDIA Nsight™ Systems
The post Optimizing Data Transfer in AI/ML Workloads appeared first on Towards Data Science.
Drift Detection in Robust Machine Learning Systems
A prerequisite for long-term success of machine learning systems
The post Drift Detection in Robust Machine Learning Systems appeared first on Towards Data Science.
EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas
How to build, score, and interpret RFM segments step by step
The post EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas appeared first on Towards Data Science.
Deep Reinforcement Learning: The Actor-Critic Method
Robot friends collaborate to learn to fly a drone
The post Deep Reinforcement Learning: The Actor-Critic Method appeared first on Towards Data Science.
Production-Ready LLMs Made Simple with the NeMo Agent Toolkit
From simple chat to multi-agent reasoning and real-time REST APIs
The post Production-Ready LLMs Made Simple with the NeMo Agent Toolkit appeared first on Towards Data Science.
The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel
AUC measures how well a model ranks positives above negatives, independent of any chosen threshold.
The post The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel appeared first on Towards Data Science.
Implementing Vibe Proving with Reinforcement Learning
How to make LLMs reason with verifiable, step-by-step logic (Part 2)
The post Implementing Vibe Proving with Reinforcement Learning appeared first on Towards Data Science.
Exploring TabPFN: A Foundation Model Built for Tabular Data
Understanding the architecture, training pipeline and implementing TabPFN in practice
The post Exploring TabPFN: A Foundation Model Built for Tabular Data appeared first on Towards Data Science.
How IntelliNode Automates Complex Workflows with Vibe Agents
Many AI systems focus on isolated tasks or simple prompt engineering. This approach allowed us to build interesting applications from a single prompt, but we are starting to hit a limit. Simple prompting falls short when we tackle complex AI tasks that require multiple stages or enterprise systems t...
Keeping Probabilities Honest: The Jacobian Adjustment
An intuitive explanation of transforming random variables correctly.
The post Keeping Probabilities Honest: The Jacobian Adjustment appeared first on Towards Data Science.