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Redis for AI and ML on JupyterHub

Data Science Dojo

Redis for AI and ML on JupyterHub

Data Science Dojo

Jupyter notebook with Redis, Redis-py, RedisJSON and RedisML

Redis for AI and ML on JupyterHub

Data Science Dojo's mission is to make data science easier, more practical, and accessible to everyone.

About the offer:

This offer will help you scale your ML infrastructure almost instantly. It's a JupyterHub for up to 100 users. It comes pre-loaded with Python and Redis. Redis is a powerful real-time data platform.

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions, and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

Popular Redis use cases include:

  • Enterprise caching
  • Session management
  • Leaderboards
  • Real-time inventory
  • Fraud mitigation
  • Claims processing

Who benefits from this offer:

This offer is designed for developers who want to realize the power of real-time ML with sub-millisecond speed at an infinite scale.

  • Great for ML on mobile
  • Quick and easy infrastructure setup
  • Pre-installed packages and libraries to get started quick

What's included in this offer: This image contains the following, all pre-installed for your convenience:

Redis

  • Redis library for Python
  • Redis Server
  • RedisJSON
  • Redis ML

JupyterHub

  • Built on the Littlest JupyterHub, allowing 1-100 users on a single machine.

Python 3.7

  • Python Libraries: numpy, scipy, matplotlib, pandas, scikit-learn, seaborn, beautifulsoup4, plotly, opencv-python, azure-storage-blob, azure-storage-file, azure-storage-queue, azure-storage-common

Technical Specifications:

  • Minimum requirements: 2 CPU, 4 GB Memory
  • Operating System: "Ubuntu 18.04"
  • Authoring Tools: Jupyter, Jupyter Lab, and Terminal
  • Users can access the VM via Remote Desktop, SSH, or browser
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