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Machine Learning Toolkit for SEO

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MLTS

Machine Learning Toolkit for SEO

Initial demo notebook here

What are the problems/needs?

What are the particular problems in the community that could be solved via machine learning.

  • Generating better titles.
  • Generating descriptions for pages. Summarization.
  • Generating alt text from images.
  • Need to get from the community.
  • Create a Twitterbot

What is the overall flow?

  • Data Getting
  • Data Cleaning and Feature Extraction
  • Iteration and Updating
  • Optimization
  • Models (train / predict)

Roles

  • Developing Use Cases
  • Evangelism / Community
  • Analytics (per Britney: Analytics)
  • Coding
  • Tutorials
  • Documentation / Readability
  • Unit Tests / Linting
  • Design

Data needs

  • Link data
  • Analytics
  • Scraping
  • Ranking data
  • Anonymous performance data

Proposed Structure

Most folders include a Todo.txt with some suggested items to start with.

  • APIs: Holds glue for various SEO APIs
  • Data: Holds datagetter classes for APIs and hosted datasets.
  • Docs: Holds the documentation for the repo.
  • Models: Holds various models that can be used to train on.
  • NPL: Glue for NLP libraries
  • Testing: Unit testing and CI
  • Tutorials: Holds iPython tutorials in Pytorch and Tensorflow
  • Config.py: Holds API keys and configuration data.
  • Main.py: The main application file.
  • requirements.txt: Python libraries needed to install via Pip.

Original concept gist: (source)

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