#Jupyter Notebook AI
124 related articles
·7 min
ManagedAgents.sh: A Deep Dive into the Model-Agnostic Open-Source Managed Agent Platform
ManagedAgents.sh is a model-agnostic managed agent platform from OpenComputer, supporting Claude, Pi, and Codex runtimes with Slack and GitHub integration.
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·7 min
Free Mermaid Diagram Editor: An Essential Code-Based Diagramming Tool for Developers
Explore the core features and use cases of the free Mermaid Diagram Editor. Supporting flowcharts, sequence diagrams, Gantt charts and more, it follows the 'diagrams as code' philosophy to enable version-controlled technical documentation for developers and architects.
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·3 min
Python for Absolute Beginners: A Complete Breakdown of a 10-Hour Systematic Course
Breaking down a 10-hour Python course for absolute beginners — covering syntax, OOP, functional programming, web scraping, and automation, with mind maps and exercises.
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·4 min
Claude Science Launch: Anthropic's AI Assistant Built for End-to-End Scientific Research
Anthropic launches Claude Science (beta), a research-focused AI app with artifact traceability, on-demand environments, and 60+ scientific database integrations.
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·6 min
AI for Beginners: A Five-Step Practical Path That Skips the Math and Python Syntax Traps
Struggling with math and Python when learning AI from scratch? This article lays out a five-step entry path: grasp the concepts, learn Python lightly, master ML and deep learning principles, get hands-on with PyTorch, then deepen understanding through real projects.
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·5 min
Python Learning Roadmap for Beginners: A Three-Stage System to Avoid 90% of Detours
Learning Python from scratch? This article breaks down the three learning stages—Fundamentals, Intermediate, and Practice—covering variables, OOP, scraping, and data analysis to help you plan a systematic Python path.
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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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·7 min
DryFox v0.3.3: AI Agent Team Collaboration + Composable UI Panels Explained
In-depth look at DryFox v0.3.3's three core features: multi-role agent team collaboration, one-click reusable team templates, and block-style composable UI panels. With Stop Hook, file mailbox comms, and hot-reload plugins.
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·2 min
Getting Started with LLMs: A Complete Roadmap from Zero to Practice
How to learn LLMs from scratch? This guide covers personalized learning paths for 3 types of learners, hardware tips (16GB RAM is enough), Python prep, and cloud GPU options.
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·2 min
Andrew Ng Partners with Anthropic: A Deep Dive into the Claude Code Practical Course
Andrew Ng and Anthropic launch a Claude Code course covering RAG chatbots, data dashboards, and Figma-to-frontend projects, with Git Worktrees and MCP server orchestration.
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·7 min
AI Agent Code Execution Sandbox Selection Guide: In-Depth Comparison of E2B and Four Other Solutions
In-depth comparison of five AI Agent code execution sandbox solutions—E2B, Daytona, Modal, Cloudflare Sandbox, and Vercel Sandbox—across isolation, cold start latency, state management, and pricing.
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·3 min
A Complete Guide to Learning Python from Scratch: From Basics to Web Scraping Projects
A systematic Python learning path for beginners covering syntax, OOP, web scraping, office automation, and data analysis, with methodology tips and resources.
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·3 min
Python Self-Study Roadmap: A Three-Phase Learning Method from Zero to Hands-On Projects
A detailed Python self-study roadmap in three phases: fundamentals, OOP & intermediate skills, and hands-on projects including web scraping and office automation.
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·3 min
Learn Python from Scratch: A Three-Phase Systematic Learning Path and Practical Guide
How to efficiently learn Python from scratch? This guide covers a three-phase learning path—fundamentals, intermediate, and practical—including environment setup, OOP, web scraping, office automation, and data analysis.
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From a Single Prompt to an AI Product:…
·3 min
From a Single Prompt to an AI Product: Starting Is Easy, Shipping Is Hard
AI startups begin with a prompt, but going from idea to product means overcoming major technical, product, and business challenges. A low barrier to entry doesn't mean a low barrier to success.
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·3 min
Paseo: A Unified Cockpit for Remotely Controlling Coding Agents from Your Phone
Paseo is a locally deployed remote console for coding Agents, enabling mobile monitoring of Claude Code, Codex, Copilot and more. Learn about its architecture, use cases, and security considerations.
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·3 min
AI Scientist: A Deep Dive into Sakana AI's Automated Research Framework
Deep dive into Sakana AI's open-source AI Scientist project: how LLMs automate the full research pipeline from hypothesis generation and experiment execution to paper writing, including architecture, workflow, and limitations.
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·3 min
Core Insights from Andrew Ng's Prompt Engineering Course: From Fundamentals to Practice
Deep dive into Andrew Ng's ChatGPT Prompt Engineering course: Base vs. Instruction Tuned LLMs, two core prompting principles, and practical developer methodologies.
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·3 min
Python Excel Automation in Practice: Data Filtering and Categorization with Pandas
Learn how to use Python Pandas to automate Excel data filtering and categorization. Core code is just 6-8 lines — handle massive datasets effortlessly.
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·2 min
Interactive Essays: A New Content Creation Paradigm Worth Diving Into
Interactive essays blend text with visualizations and simulators for active learning. Explore their definition, cognitive science benefits, AI-era opportunities, and how to get started.
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