#learn to code
4961 related articles
·3 min
Getting Started with MARL (Multi-Agent Reinforcement Learning): A Complete Path from Theory to Code
A systematic guide to learning MARL from theory to code, covering CleanRL, PettingZoo, PyMARL tools, IQL/VDN/QMIX/MADDPG algorithm progression, and practical tips for bridging theory and implementation.
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·3 min
Learning to Code in the AI Era: The Worst and Best of Times
AI coding tools are reshaping software development. Is learning to code still worthwhile? This article analyzes the challenges and opportunities of learning programming in the AI era.
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·3 min
Zero-Code Research: Using AI Agents to Run Complete Machine Learning Experiments
No coding required: use AI agents like Codex and Claude Code to complete full ML experiments via natural language. A real case study with a heart disease dataset.
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·3 min
No-Code Research: Using AI Coding Tools to Complete the Full Machine Learning Pipeline
No coding skills? No problem. Learn how AI tools like Codex and Claude Code let researchers complete ML workflows — data cleaning, model training, visualization — using only natural language.
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·4 min
Do You Still Need to Hand-Code Machine Learning Algorithms in the AI Era? The Answer and the Method
With AI tools everywhere, is it still worth hand-coding SVM, decision trees, and other ML algorithms? This article explores the real value of hand-coding, the limits of AI tools, and smarter learning strategies for beginners in the AI era.
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·2 min
VersatIL: A Modular PyTorch Framework Tackling Code Fragmentation in Imitation Learning
VersatIL is a modular PyTorch framework for robot imitation learning that decouples data, network architecture, algorithm, and objective. Supports ACT, Diffusion Policy, pi0, and LeRobot format.
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·1 min
Four Weeks to AI Coding: A Complete Learning Path for Codex and AI Agents
How to learn AI coding from scratch? This article breaks down a four-week framework for Codex and AI Agents: master core skills, build workflows, develop Agents, and complete real projects.
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·4 min
YOLO Learning Roadmap: From Version Evolution to Source Code Deep Dive
A systematic YOLO learning roadmap: from understanding V1/V3/V4 version evolution, to building knowledge via video, to mastering implementation by debugging source code.
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·4 min
Learn to Code with AI from Scratch: A Complete Learning Path from Beginner to Deployment
A complete learning path for coding with AI from scratch — from concepts and environment setup to using Cursor, Claude, and other AI tools to build and deploy your first project.
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·3 min
Getting Started with Claude Code: An AI Programming Tool Anyone Can Learn Quickly
A complete guide to Claude Code: installation, setup, natural language programming, CLAUDE.md configuration, real-world use cases, and pricing plans for beginners.
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·2 min
Claude Code Chinese Tutorial: A 100-Page Systematic Learning Guide on Feishu Docs
A detailed look at the Claude Code Chinese learning resource on Feishu Docs, covering AI agent learning, memory systems, and task decomposition with a systematic path from beginner to advanced.
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·4 min
Claude Code Practical Guide: Deep Dive into 7 Core Modules with Learning Path
Deep dive into Claude Code's 7 core modules: project integration, agent construction, multi-agent collaboration, plugin systems, and workflow automation, with learning tips and certification trends.
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·2 min
Claude Code vs ByteDance Codex: A Guide to Chinese Learning Resources and Choosing the Right Tool
Compare Claude Code and ByteDance Codex: their positioning, core capabilities, and use cases. Includes Chinese learning resource recommendations and beginner path selection guide for AI programming.
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·3 min
Codex Beginner's Guide: Lessons Learned from 660 Million Tokens of Real-World Usage
Deep dive into OpenAI Codex Agent's core features, Skill ecosystem, context compression, and project-level Harness management tips from 660M tokens of real-world usage.
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Expert Opinions·3 min
Is Learning to Code Still Worth It in the AI Era? An Honest Answer from an Atlassian Engineer
Can AI write code instantly—so is coding still worth learning? An Atlassian engineer breaks down the truth behind tech leaders' claims and AI coding limitations.
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Tutorials·3 min
Efficient PyTorch Learning: A Source Code-Driven Methodology
A proven PyTorch learning method: spend 2-3 days on basics, then advance rapidly by reading U-Net and ViT source code line by line. Master PyTorch through source code-driven learning.
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Tutorials·3 min
Full-Stack Development for Beginners in the AI Era: Don't Write Code — Learn to Manage It
AI coding tools make code generation easy, but a huge gap remains between code and product. This article breaks down frontend, backend, and DevOps stacks, exploring how beginners can manage code with AI.
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Tutorials·2 min
Python Machine Learning in Practice: A Complete Guide from Algorithm Derivation to Code Implementation
A systematic Python ML course using a 3-stage framework: algorithm derivation, code implementation, and experimental analysis. Covers logistic regression, decision trees, and ensemble learning.
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Deep Dives·6 min
learn-claude-code: Deep Dive into the 58K-Star AI Agent Framework
Deep analysis of the 58K-Star open-source project learn-claude-code: building a Claude Code-like programming agent from scratch. Deconstruct the Agent Harness, ReAct loop pattern, and Bash execution layer.
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·3 min
Soup CLI: An Open-Source Tool That Fine-Tunes 8-Billion Parameter LLMs on a 4GB GPU — A Deep Dive
Soup CLI is an open-source CLI tool that uses layer-by-layer streaming to fine-tune 8B parameter LLMs like Llama-3.1-8B on laptop GPUs with just 4GB VRAM.
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