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)