
Sales Forecasting with Python Machine Learning
・Skills: Python, Machine Learning, Pandas
・Overview: A project that automates sales forecasting using Python machine learning.
Portfolio
In this project, I built a system that automatically generates high-quality blog articles using AI. The system automates and streamlines everything from target keyword selection to HTML generation, with a focus on quickly providing content that addresses user concerns. The ultimate goal is to achieve top Google search rankings for each article's target keywords.
List and manage target keywords in Google Sheets.
Use LangGraph to create multiple personas and conduct interviews with them. Based on the interview results, I identify pain points and needs related to each keyword. This information is then used to create detailed requirement specifications (instruction documents) for each blog article.
Utilize Python's Jinja library to dynamically generate HTML templates for articles. This allows for efficient creation of HTML with a consistent underlying structure.
Create article content in Cursor and refine it by combining multiple AI models. The completed text is then incorporated into the HTML code generated with Jinja to finalize the article.
Through this blog article creation workflow utilizing AI and automation, I've made it possible to efficiently handle everything from keyword research to HTML code generation. I continue to optimize the process to achieve higher search engine rankings.
Moving forward, I plan to implement various techniques to further enhance blog article quality. Currently, the workflow includes some manual operations, requiring about 30 minutes of work time for 10 articles. My goal is to make the process even more efficient and reduce human involvement to the absolute minimum.

・Skills: Python, Machine Learning, Pandas
・Overview: A project that automates sales forecasting using Python machine learning.

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・Skills: Python, LangChain/LangGraph, Google Cloud
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