#Python vector index
211 related articles
·2 min
awesome-systematic-trading: A Complete Guide to the 9,000-Star Quantitative Trading Open Source Resource List
Deep dive into the 9,100-star awesome-systematic-trading GitHub project covering backtesting frameworks, strategy implementations, data tools, and classic books for quantitative traders.
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·2 min
book-to-skill: An Open-Source Tool That Converts Technical Book PDFs into Claude Code Skills
book-to-skill is an open-source GitHub project with over 10K stars that converts technical book PDFs into Claude Code Skills, enabling AI coding assistants to directly leverage book knowledge.
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·6 min
Harness Engineering: From Context Engineering to the Third Phase of AI Programming
Explore Harness Engineering: the next evolution beyond context engineering for AI programming. Learn how to build enterprise-grade Skill systems and deliver real projects with mid-tier models.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·3 min
Backend Developer Transition to AI/LLM: 4 Core Skills and a Practical Learning Roadmap
Complete guide for backend developers transitioning to AI/LLM engineering. Covers the 4 core skills—Python, RAG, Fine-tuning, and Agents—with a phased learning roadmap and practical project advice.
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·3 min
Spring AI Explained: Unified API, RAG, and Enterprise AI Development Guide
Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.
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·3 min
Spring AI Explained: Unified API, RAG, and Enterprise AI Development Practical Guide
Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.
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·3 min
Replacing spaCy's Sentencizer with yasbd: Accuracy Jumps from 55% to 98.9%
spaCy's default Sentencizer achieves only 55.4% accuracy on edge cases, while open-source library yasbd reaches 98.9%. Analysis of limitations and integration code examples.
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·5 min
A Beginner's Guide to Prompt Engineering: From One-Off Instructions to a Systematic Methodology
A beginner's guide to prompt engineering covering the four functions of prompts, the key differences from prompt engineering, a six-step systematic workflow, and critical technical and practical limitations.
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·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
Learn AI Agent core principles from scratch: understand how Agents differ from LLMs, their execution mechanisms, why rule design matters, and find the right learning path for your goals.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
A beginner's guide to AI Agents: understand core principles, how Agents differ from LLMs, their execution mechanisms, and get tailored learning path recommendations.
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·4 min
FPGA Softmax Approximation in Practice: A Detailed Guide to Taylor Expansion and Padé Approximation Methods
A detailed guide on efficiently implementing Softmax on FPGAs, comparing Taylor series and Padé approximation methods for accuracy and resource trade-offs, with Python simulation and range reduction techniques.
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·3 min
Spring AI Alibaba Graph in Practice: Building a Full-Process HR Recruitment Agent
A detailed guide on building a full-process HR recruitment Workflow Agent with Spring AI Alibaba Graph, covering resume parsing, multi-dimensional screening, tiered questions, human-in-the-loop, and state rollback.
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·4 min
Spring AI 2.0: Five Key Updates Explained — Marching Toward the Age of AI Agents
Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, Tools parsing moving up, a built-in Agentic mechanism, MCP switching to Streamable HTTP, and an on-demand tool Advisor.
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·4 min
Spring AI 2.0 Explained: Five Key Updates Ushering in the Age of AI Agents
Spring AI 2.0 brings five core updates: mandatory Spring Boot 4 upgrade, Tools parsing moved up, built-in Agentic mechanism, MCP switch to Streamable HTTP, and on-demand tool-loading Advisor.
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·4 min
Spring AI 2.0: Five Key Updates Explained — Stepping into the Agent Era
Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, lifted Tools parsing, built-in Agentic mechanism, MCP switch to Streamable HTTP, and an on-demand tool-loading Advisor.
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·3 min
Multi-Agent AI Paper Writing System: A Full-Stack Breakdown of FastAPI + Vue3
A deep dive into an AI paper writing system built with FastAPI + Vue3, covering multi-agent collaboration, RAG, streaming output, and full academic workflow automation.
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·4 min
Spring AI 1.0 Practical Guide: A Java Developer's Fast Track to Building AI Applications
Spring AI 1.0 is here — Java developers can now build AI apps without switching to Python. This guide covers LLM integration, RAG, intelligent customer service, and Agent patterns for enterprise deployment.
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·5 min
From Vibe Coding to AI Engineering: A Complete Guide to Enterprise-Grade Development
In the AI programming era, Vibe Coding alone can only build toys. This article deeply analyzes the complete engineering path from Vibe Coding to SDD spec-driven development, covering Claude Code and Codex tool selection, the SuperPower plugin, and domestic LLM comparisons.
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