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IT Services Circle
IT Services Circle
Jan 2, 2026 · Artificial Intelligence

Top Open‑Source NotebookLM Alternatives: AI‑Powered Docs, Podcasts & Research Tools

This article surveys the most popular open‑source replacements for Google NotebookLM, detailing each project's star count, supported AI models, multimodal input capabilities, Docker deployment options, and unique features such as multi‑speaker podcast generation, semantic search, and collaborative knowledge‑base integration.

DockerLLMMultimodal
0 likes · 8 min read
Top Open‑Source NotebookLM Alternatives: AI‑Powered Docs, Podcasts & Research Tools
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Sep 22, 2025 · Big Data

How Dataverse’s Notebook Supercharges Data+AI Development at Xiaohongshu

The article details Xiaohongshu’s Dataverse platform evolution into a Data+AI system, highlighting inefficiencies in algorithm and data‑science workflows, the introduction of an interactive notebook, comprehensive data lineage, AI‑coding assistance, and future DataAgent plans to automate data engineering tasks.

AI CodingData LineageData Platform
0 likes · 21 min read
How Dataverse’s Notebook Supercharges Data+AI Development at Xiaohongshu
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 24, 2025 · Big Data

Master DataWorks Notebook: Interactive SQL & Python for Big Data Development

This guide walks you through setting up a personal DataWorks Notebook, performing interactive SQL development with engines like MaxCompute, creating Python visualizations, building ipywidgets for dynamic queries, and leveraging the AI‑powered Copilot to rewrite, explain, and comment code, all within a unified big‑data platform.

Big DataCopilotDataWorks
0 likes · 9 min read
Master DataWorks Notebook: Interactive SQL & Python for Big Data Development
Programmer DD
Programmer DD
Jul 13, 2023 · Artificial Intelligence

Unlock Interactive Kotlin Development with the New Kotlin Notebook Plugin

IntelliJ IDEA's Kotlin Notebook plugin brings interactive notebooks to Kotlin, enabling developers to combine code, visualizations, and narrative in a single document, supporting rapid prototyping, data analysis, and AI workflows with seamless library integration and flexible execution controls.

Data ScienceIntelliJ IDEAInteractive Development
0 likes · 4 min read
Unlock Interactive Kotlin Development with the New Kotlin Notebook Plugin
Architecture Digest
Architecture Digest
Jul 4, 2023 · Fundamentals

JupyterLab 4.0: New Features, Performance Boosts, and Extension Management

JupyterLab 4.0 introduces a flexible multi‑document interface, customizable layouts, an integrated file browser, modular extensibility, built‑in terminal, significant performance improvements, a separate real‑time collaboration package, and a PyPI‑based extension manager, while noting that AI‑assisted coding tools may now outpace it.

Data ScienceExtensionsIDE
0 likes · 4 min read
JupyterLab 4.0: New Features, Performance Boosts, and Extension Management
Cloud Native Technology Community
Cloud Native Technology Community
Jun 28, 2023 · Artificial Intelligence

Building and Deploying Custom Large Language Models with Alauda Cloud‑Native MLOps

This article explains how enterprises can use the Alauda MLOps platform to quickly set up, fine‑tune, and deploy private large language models on cloud‑native infrastructure, covering notebook preparation, GPU allocation, model download, inference service creation, distributed training pipelines, and Docker image building.

Fine-tuningMLOpsai
0 likes · 9 min read
Building and Deploying Custom Large Language Models with Alauda Cloud‑Native MLOps
Python Programming Learning Circle
Python Programming Learning Circle
Aug 13, 2021 · Fundamentals

JupyterLab 3.0: New Features, Installation Options, and Extension Improvements

JupyterLab 3.0 introduces a visual debugger, directory extension, multilingual UI, enhanced simple‑mode, better mobile support, and pre‑built extensions, while offering three installation methods (pip, mamba, conda) and streamlined workflows for extension authors, making the notebook environment more powerful and user‑friendly.

DataScienceInstallationJupyterLab
0 likes · 6 min read
JupyterLab 3.0: New Features, Installation Options, and Extension Improvements
21CTO
21CTO
Jun 27, 2021 · Fundamentals

Boost Your Jupyter Workflow: How Jupytext Bridges Notebooks and IDEs

Jupytext lets you convert Jupyter Notebooks to plain‑text formats, enabling seamless version control and IDE editing while preserving the visual advantages of notebooks, making data‑science projects more manageable and collaborative.

IDE integrationJupyterJupytext
0 likes · 6 min read
Boost Your Jupyter Workflow: How Jupytext Bridges Notebooks and IDEs
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 20, 2020 · Big Data

Getting Started with Apache Zeppelin: Installation, Core Features, and Integration with JDBC, Spark, and Flink

This tutorial introduces Apache Zeppelin, explains REPL and Jupyter concepts, outlines its core features and project structure, and provides step‑by‑step instructions for installing Zeppelin, creating notebooks, and connecting to databases, Spark, and Flink with practical code examples.

Apache ZeppelinFlinkInstallation
0 likes · 11 min read
Getting Started with Apache Zeppelin: Installation, Core Features, and Integration with JDBC, Spark, and Flink
Meituan Technology Team
Meituan Technology Team
Nov 21, 2019 · Big Data

Designing a Platformized Jupyter Service Integrated with Spark for Meituan

Meituan Homestay created a platform‑wide Jupyter service built on JupyterHub and Kubernetes that integrates Spark, scheduling, documentation and storage, providing seamless, reproducible notebooks with custom extensions, magics and container isolation to unify data analysis, model training and production workflows.

Big DataJupyterKubernetes
0 likes · 19 min read
Designing a Platformized Jupyter Service Integrated with Spark for Meituan
MaGe Linux Operations
MaGe Linux Operations
Nov 2, 2017 · Fundamentals

Create a Stunning Jupyter Notebook Setup: Install, Configure, and Customize

This guide walks you through installing Jupyter via Anaconda, configuring IPython profiles, customizing Matplotlib for inline and Chinese font support, optimizing Retina displays, tweaking notebook CSS, and adding useful extensions like nbextensions and dashboards to create a polished, production‑ready environment.

ConfigurationExtensionsIPython
0 likes · 8 min read
Create a Stunning Jupyter Notebook Setup: Install, Configure, and Customize