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2024

Introduction to Using Redivis

Redivis is a powerful data querying and analysis platform built specifically with researchers in mind. It is currently the GSB's solution for hosting Big Data (data on the scale of TBs) for researchers at the school. At the time of this post, the StanfordGSBLibrary Redivis organization hosts more than 50 datasets consisting of over 100 TB of data with 300 organization members.

If you are a researcher who is just starting to use Redivis, or considering using the platform, this blog post will help you get started by covering some common use cases and helpful tips.

Train Machine Learning Models on Colab GPU

Google Colab

Google Colab enables you to run Jupyter notebooks in the cloud with the option to use a CPU or accelerate computations by adding GPU or TPU support. We will use the free Colab tier, but for longer training jobs or access to better GPUs (e.g., T4, P100, or V100), the paid Colab Pro or Colab Pro+ option may be a better choice. Navigate to Colab website and check out an example Jupyter notebook that uses a GPU for machine learning training.

Reproducible Research Essentials

This guide provides the foundational components needed to ensure reproducibility in your research. It focuses on:

  • Documentating fixed inputs and expected outputs
  • Making a README file
  • Managing computational environments
  • Summary with additional resources
  • Advanced topics