Avoiding Overfitting, Class Imbalance, & Feature Scaling Issues: The Machine Learning Practitioner’s Notebook
Machine learning practitioners encounter three persistent challenges that can undermine model performance: overfitting, class imbalance, and feature scaling issues.
Topic Modeling Techniques for 2026: Seeded Modeling, LLM Integration, and Data Summaries
Seeded topic modeling, integration with LLMs, and training on summarized data are the fresh parts of the NLP toolkit.
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LLMs like ChatGPT, Claude, and Gemini, are often considered intelligent because they seem to recall past conversations. The model acts as if it got the point, even after you made a follow-up question. This is where LLM memory comes in handy. It allows a chatbot to go back to the point of what “it” o...
If you are searching for free LLM APIs, chances are you already want to build something with AI. A chatbot. A coding assistant. A data analysis workflow. Or a quick prototype without burning money on infrastructure. The good news is that you no longer need paid subscriptions or complex model hosting...
From ‘Dataslows’ to Dataflows: The Gen2 Performance Revolution in Microsoft Fabric
Dataflows were (rightly?) considered "the slowest and least performant option" for ingesting data into Power BI/Microsoft Fabric. However, things are changing rapidly and the latest Dataflow enhancements changes how we play the game
The post From ‘Dataslows’ to Dataflows: The Gen2 Performance Revolu...
Under the Uzès Sun: When Historical Data Reveals the Climate Change
Longer summers, milder winters: analysis of temperature trends in Uzès, France, year after year.
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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
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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
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Hackathons are different!. The good ones pull you in, stretch your thinking, and leave you with something real—regardless of the outcome. The problem is choice. It’s hard to find the right one! Too many hackathons. Too many formats. And too much noise. So this list is built with that in mind. Instea...
Federated Learning, Part 1: The Basics of Training Models Where the Data Lives
Understanding the foundations of federated learning
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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.
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If you’re curious about trending terms like AI Agents or Agentic AI, you’re in the right place. Agentic AI is rapidly moving from experimentation to enterprise adoption. According to Gartner, over 60% of enterprise AI applications are expected to include agentic components by 2026, while more than 4...
NyRAG: Building Production-Ready RAG Applications with Zero Code
Retrieval-Augmented Generation (RAG) technology almost immediately became the standard in intelligent applications. This was a result of the quickly developing field of artificial intelligence that combined large language models and external knowledge bases with different real-time access methods. R...
The name Google has always been synonymous with technology, and things are no different in the age of AI. Google has quietly been the frontrunner in the AI revolution with a host of products that surprisingly few people know about. Of course, the showstoppers like Gemini and NotebookLM have been pop...
Beyond Prompting: The Power of Context Engineering
Using ACE to create self-improving LLM workflows and structured playbooks
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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...
10 Most Popular GitHub Repositories for Learning AI
The most popular GitHub repositories to help you learn AI, from fundamentals and math to LLMs, agents, computer vision, and real-world production systems.