Launch HN: Deepnote (YC S19) – A better data science notebook
📰 Hacker News · Equiet
Learn how to improve data science workflows with Deepnote, a new data science notebook that addresses pain points in versioning, reproducibility, and collaboration
Action Steps
- Explore Deepnote's features at https://deepnote.com/
- Compare Deepnote with existing data science notebooks
- Try building a data science project using Deepnote
- Evaluate Deepnote's collaboration features for team projects
- Configure Deepnote to integrate with other tools in your workflow
Who Needs to Know This
Data scientists and engineers can benefit from Deepnote's features, which aim to improve collaboration and best practices in data science workflows
Key Insight
💡 Deepnote aims to address pain points in data science notebooks, such as versioning, reproducibility, and collaboration, to create a better computational medium
Share This
💡 Improve data science workflows with @Deepnote! 📊💻
Key Takeaways
Learn how to improve data science workflows with Deepnote, a new data science notebook that addresses pain points in versioning, reproducibility, and collaboration
Full Article
Hello HN, I'm Jakub and I'm the founder of Deepnote ( https://deepnote.com/ ). We're building a better data science notebook. As an engineer, I spent most of my time working on developer tools, building IDEs, and studying human-computer interaction. I helped build a couple of startups, I built tools for JavaScript development, and worked on Firefox DevTools. But once I started to work with data scientists, all those code editors and IDEs that I knew as a software engineer suddenly stopped being the right tool for the job. Notebooks were. Notebooks as we know them today have many pain points (versioning, reproducibility, collaboration). They don't work well with other tools. They don't exactly encourage best practices. But none of these are fundamental flaws of the notebook paradigm. They are signs of a new computational medium. Much like spreadsheets in the 1980s. Two years ago, my co-founders and I started to think about a better data science no
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