Tags: visualization*

Visualization is the process of representing data or information in a graphical or visual format, making it easier to understand and interpret. In the context of scientific and technical computing, visualization is often used to help analyze and communicate complex data, patterns, trends, and relationships. It can be applied in various fields such as data science, machine learning, and deep learning.

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  1. PySpecSDR is a Python-based Software Defined Radio (SDR) spectrum analyzer with real-time visualization, demodulation, and signal analysis capabilities.
  2. A tutorial on creating a scatterplot using text instead of dots, focusing on simplicity and quick reference.
  3. A guide on how to use OpenAI embeddings and clustering techniques to analyze survey data and extract meaningful topics and actionable insights from the responses.

    The process involves transforming textual survey responses into embeddings, grouping similar responses through clustering, and then identifying key themes or topics to aid in business improvement.
  4. A visual representation of papers on ArXiv using UMAP and nomic-embed.
    2024-10-12 Tags: , , , , , by klotz
  5. A map of math articles from ArXiv using t-SNE and nomic-embed.
    2024-10-12 Tags: , , , , , by klotz
  6. Mermaid is a JavaScript-based diagramming and charting tool that renders Markdown-inspired text definitions to create and modify complex diagrams. It enables users to create easily modifiable diagrams and integrates with various applications.
  7. A step-by-step guide on understanding and implementing t-SNE for visualizing high-dimensional data using Python.
  8. This article details a data-driven exploration of owl species, using Wikipedia data to create a network visualization of owl relationships.
  9. DeepMind's Gemma Scope provides researchers with tools to better understand how Gemma 2 language models work through a collection of sparse autoencoders. This helps in understanding the inner workings of these models and addressing concerns like hallucinations and potential manipulation.
  10. Shiny for Python lets you build interactive web applications with ease. It utilizes reactive programming for efficient and dynamic visualizations.

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