I'm the maker of Hacker-AI. Here's a little bit of details and background to the tool.
I have a decade-long background working as a marketing/tech consultant. I've used a similar approach in my projects to save time and remove uncertainty when choosing the content for eg. marketing campaigns or product launches. I have learned how to create tools like this first for myself, but I've also implemented similar tools for companies so that their content and marketing team can perform more effectively.
I'm not a data scientist and this tool is a result of learning from smart people and experimenting with different machine learning and NLP solutions. It uses a combination of feed-forward neural network and bag-of-words analysis to conduct the predictions. In my tests it was able to predict correctly 60%-70% oft times which variation got more points in Hacker News or upvotes in Product Hunt (when using texts that resemble the platform's style). It uses data from Hacker News API and Product Hunt API for training the prediction models.
I'm the maker of Hacker-AI. Here's a little bit of details and background to the tool.
I have a decade-long background working as a marketing/tech consultant. I've used a similar approach in my projects to save time and remove uncertainty when choosing the content for eg. marketing campaigns or product launches. I have learned how to create tools like this first for myself, but I've also implemented similar tools for companies so that their content and marketing team can perform more effectively.
I'm not a data scientist and this tool is a result of learning from smart people and experimenting with different machine learning and NLP solutions. It uses a combination of feed-forward neural network and bag-of-words analysis to conduct the predictions. In my tests it was able to predict correctly 60%-70% oft times which variation got more points in Hacker News or upvotes in Product Hunt (when using texts that resemble the platform's style). It uses data from Hacker News API and Product Hunt API for training the prediction models.
The open-source technologies I've used are: https://github.com/andreekeberg/ml-classify-text-js https://brain.js.org/#/
An example of the neural network's client-side implementation is available in this Github repo (old layout). https://github.com/ihmissuti/hacker-ai
All feedback, questions, or ideas I could make this tool better are highly welcome.