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Towards Data Science
Jul 27, 2026
Reducing Human Annotation with ML Active Learning
In a world where human time is expensive, learn how to use it only when really necessary
The post Reducing Human Annotat…
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ML Mastery
Jul 20, 2026
Building Agentic Workflows in Python with LangGraph
In this article, you will learn how to build a complete agentic workflow in Python with LangGraph, from a single model c…
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Towards Data Science
Jul 26, 2026
How to Give an LLM Agent a Browser
Building a browser-use agent with OpenAI Agents SDK and Playwright MCP
The post How to Give an LLM Agent a Browser appea…
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ML Mastery
Jul 17, 2026
Agentic AI Security: Defending Against Prompt Injection and Tool Misuse
In this article, you will learn what prompt injection and tool misuse are in the context of agentic AI systems, and whic…
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Towards Data Science
Jul 25, 2026
How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes
Architecting cost-effective infrastructure by navigating the latency and storage trade-offs of HNSW, SPANN, and DiskANN
…
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Towards Data Science
Jul 24, 2026
Context Windows Forget What Matters — I Built a Usage-Reinforced Decay Engine for AI Agent Memory
Most AI memory systems keep the newest information—not the most important. Here's how I used the Ebbinghaus forgetting c…
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Towards Data Science
Jul 28, 2026
MCP Explained: How Modern AI Agents Connect to the Real World
from custom integrations to a universal standard for tool access
The post MCP Explained: How Modern AI Agents Connect to…
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Towards Data Science
Jul 23, 2026
Most RAG Hallucinations Are Extraction Errors: Seven Patterns for a Typed Generation Contract
Enterprise Document Intelligence [Vol.1 #8ter] - Naming the RAG error correctly matters: model reads the context, so a w…
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