NetBook
  • The Basics
    • About
      • 🧑‍🤝‍🧑Community
    • 🔰Getting Started
      • 🤟Introduction
    • 🛒Components
      • ⚒️WorkFlow
      • 👨‍🏫Projects
      • 🟩Dashboard
      • 🌐Workspaces
        • Overview
        • Quickstart
      • ⛏️Experiments
        • Setting Up your Code
        • Creating Training Docker Image
        • Training Data Setup
        • Start a New Training Job on NetBook UI
      • 🖥️Compute Backends
        • Add your Kubernetes Clusters
          • Create Kubernetes Cluster on E2E Nodes
          • Creating Kubernetes Cluster on Bare Metal Servers
      • 🧑‍💻Environments
        • Overview
        • Quickstart
    • 💳Accounts
      • 🌥️Bring your own Cloud
        • Azure
          • Setup in your Azure
          • Adding Credentials to Netbook Portal
        • AWS
          • Setup in your AWS account
          • Adding Credentials to NetBook Portal
    • 💵Billing
    • 🔧Settings
  • Api Docs
    • Api documentation
  • Issues and resolutions
    • Slack Support
  • Release Notes
    • Version 0
  • OpenSource
    • Docs
      • Spawner
        • reference
          • Cluster
          • Nodes
        • Setup
        • Usage examples
        • Issues and Troubleshooting
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  1. The Basics

About

NetBook is built to truly abstract out the infrastructure layer and remove compute bottle necks from Data Science workflows. Making Kubernetes more Pythonic and easy to Data Scientists is our mission

NextCommunity

Last updated 3 years ago

Product

We took a SaaS first approach to enable easier compute management for Data Scientists. But we will soon rollout an easy CLI and Python SDK to integrate NetBook's compute management within your code workflows.

We also actively engage with our community to get feedback and provide support to the issues you might face while using NetBook. You can learn more about it here.

Team

We are a team of ex-Data Scientists who worked as ML engineers, Backend Developers who built scalable solutions for Unicorns.

Opensource

We want to make sure our entire code is easily usable to all the Data Scientists and are planning to bring out all the components that make our platform work as open source. We are in the process of doing so. You can find our github account

Community
here