Log of Machine Learning work and experiments

  • tensorflow resources
  • Built a “heroku for machine learning” platform to easily train,measure performance, and convert models into APIs. Got a few paying customers on it, but used primarily for my own model experimentation
  • Ran and gave talk: “ML for artist conf day” at Bocoup Boston
  • Built custom deep dream models to hallucinate anything
  • constructed a RNN model based off of all of Helen Keller’s books to see if I could get a model to speak in a style similar to her
  • Used deep learning to parse images and automatically turn text links and emails into clickable links . The project was launched on the client’s production site processing ~5,000 images/day.
  • built internal emailing software to generate leads using multi-arm bandits.
  • Developed a social media software suite that crawls social media networks and generates features fed into a random forest classifier to predict who is interested in networking with you. Wrote the whole thing in 2 days. It generated several years of income with near zero maintenance.
  • Seung Neuroscience Lab MIT – worked on obtaining more human created training data to feed into convolutional neural networks to classify brain tissue segments, a meta loop!
  • TrueLens – developed and wrote hundreds of experiments using bayesian classifiers, SVMs, NNs, Logistic Regression, Random Forest, etc to mine and combine buying history with social data. The main goal was find out if we could use public social data to optimize offline buying habit, answer: yes.
  • Socmetrics – Started a company around the idea to mine social media data. Built a people web crawler and search engine using a simplified version of PageRank and tf-idf algorithm. Raised money for this from Google Ventures and others. Got dozens of companies paying for a subscription.
  • cld – ruby gem for fast language detection using Chrome language parser

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