#Python tutorial review
160 related articles
·6 min
AI Agent Development Learning Path: Four Stages from Zero to Hands-On Projects
A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.
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·4 min
Learn ML Free at Public Libraries: A Complete Guide to O'Reilly Tech Book Resources
Getting O'Reilly machine learning books free at public libraries? It's no myth. This article reveals hidden tech learning resources at libraries, including online platform subscriptions and digital database access, helping self-learners build AI knowledge at zero cost.
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·4 min
Coze in Practice: A Complete Guide to Building Multi-Agent Collaboration Teams
A systematic guide to Coze's positioning and capabilities, covering Agent-building platform categories, Skill modules, workflow orchestration, and multi-Agent team building.
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·4 min
Making Money with AI Coding Gigs: Platform Selection, Pitfall Avoidance, and a Rational Guide to Getting Started
AI coding tools have dramatically lowered the barrier to freelance gigs, but what risks lurk behind claims of "earning over 10,000 a month"? This article breaks down platform tiering on Zhubajie, Upwork, and more, plus three key pitfalls for beginners.
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·5 min
Getting Started with LangGraph: Building AI Agent Workflows with Graph Structures
Master LangGraph core concepts: nodes, edges, and routing functions. Learn StateGraph, MemorySaver, and ToolNode through a weather-query Hello World example, and understand how LangGraph relates to LangChain and powers Agent workflows.
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·4 min
No Competitive Programming Required: How CS Students Can Pivot to AI/ML and Land Internships
How can CS students who dislike competitive programming systematically pivot to AI/ML? This guide covers skill priorities (Python/SQL/ML/deployment), portfolio strategy, Kaggle tips, and real paths to landing AI/ML internships.
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·4 min
AI Agents Powering the Full Research Pipeline: A Practical Guide to Automation from Topic Selection to Publication
Learn how to use AI Agents to link the entire research pipeline—from literature management, data analysis, and paper writing to scientific illustration and dissemination—building a reusable research automation workflow with NotebookLM, N8N, and Ollama.
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·6 min
Grok 4.5 Hands-On: A Faster, Cheaper Coding Dark Horse — Can It Replace Opus and GPT?
In-depth Grok 4.5 hands-on review: priced at a fraction of Opus 4.8, twice the token efficiency of peers, and coding ability in the top tier. A real-project breakdown of its strengths, highlights, and shortcomings.
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·5 min
The Complete OpenCode Tutorial: Installation, Commands, and Advanced Practice
Systematically learn the OpenCode AI programming tool: covering both desktop and WSL installation, core commands, model and rule configuration, MCP integration, and Agent Skills.
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·5 min
Runs on Low VRAM! A Hands-On Look at the ID LoRA Face-to-Video Workflow
A face-to-video workflow built on GGUF quantized models and ID LoRA runs on just an RTX 3060 with 6GB VRAM. This article breaks down its core principles, four-step process, and how it tackles facial consistency in AI video.
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·5 min
28 Enterprise-Grade AI Agent Projects: A Complete Guide That Even Beginners Can Deploy
A collection of 28 fully reproducible enterprise-grade AI Agent projects covering code debugging, financial analysis, customer service, and multi-agent collaboration—deployable even for beginners.
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·4 min
AI Agent Development Deep Dive: Opportunities, Real Entry Barriers, and Learning Paths
A deep dive into AI Agent development: real architecture, entry barriers, and learning paths. From ReAct to multi-agent systems and LangChain — cut through the hype.
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·4 min
8-Step AI Agent Development Guide: From Zero to Production
Demo works but production fails? This guide covers the full AI Agent development path: when to use Agents, hand-writing ReAct loops, tool schemas, RAG, eval sets, and production fallback strategies.
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·6 min
The Truth About "GPT-5.6": Debunking Fake Rumors and Third-Party Top-Up Scams
The rumored "ChatGPT 5.6 release" is fake—OpenAI never launched it. Learn about account security risks of third-party top-ups, the truth behind low-price scams, and how to spot AI misinformation.
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·7 min
Getting Started with LangChain: The Core Framework Connecting LLMs and AI Applications
A deep dive into LangChain's positioning and value—why do LLMs need a middle layer? How does LangChain serve as the 'glue' unifying multi-model interfaces and supporting Agent development? Learn its core modules and learning path.
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·7 min
Zero-Basis Learning Path for AI Agents: A Three-Stage Journey from Beginner to Deployment
A systematic zero-basis learning path for AI Agent development, covering Python and LLM fundamentals, five core capabilities like task planning and RAG, and LangChain hands-on practice.
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·8 min
Python Web Scraping for Beginners: How It Works, Core Workflow, and Legal Red Lines Explained
A plain-language guide to how Python web scrapers work: from HTTP requests and responses, HTML tag parsing, to the complete three-step data scraping workflow, with a focus on the three legal red lines and compliance advice.
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·7 min
Learning Python from Scratch: A Complete Guide to the Three-Stage Learning Path
Want to learn Python from scratch but don't know where to begin? This article breaks down three stages—basic syntax, advanced mastery, and hands-on practice—with real projects in crawling, automation, and data analysis to help you build programming thinking.
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·6 min
video-use: The Open-Source Tool That Lets AI Coding Agents Auto-Edit Videos
video-use from the browser-use team lets AI coding Agents auto-edit videos via natural language. 13K+ GitHub stars, batch processing, silence removal, FFmpeg integration.
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·6 min
Claude Code Chinese Guide: A Complete Path from Zero to an Efficient Workflow
A systematic Claude Code learning guide built for Chinese developers, covering ten core modules including Slash Commands, Memory, MCP, and Hooks, with a three-tier path to build an AI coding workflow in 11–13 hours.
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