Peter Harrington
Co-Founder And CTO at LexText.AI
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolPeter Harrington is a seasoned technology leader and founder with 15 years of experience building production-grade predictive analytics, machine learning, and NLP systems, now serving as Co-Founder and CTO of LexText.AI in the San Francisco Bay Area. He has led end-to-end data product development—from real-time forecasting engines and information extraction to entity linking—at companies like HG Data and Zillabyte, and applied ML to semiconductor design and test at Micron. Comfortable across the stack, he pairs deep algorithmic expertise (signal processing, statistical learning, NLP) with embedded and analog systems experience from Intel and Cleanwave, enabling pragmatic solutions for both hardware and software challenges. An active contributor to practical ML tooling, he significantly enhanced the widely referenced "Machine Learning in Action" codebase by implementing core algorithms in Python. He holds advanced degrees in electrical engineering and software engineering, and is known for turning complex research into scalable, cost-effective products.
15 years of coding experience
17 years of employment as a software developer
MSEE Electrical Engineering, MSEE Electrical Engineering at Arizona State UniversityMasters of Liberal Arts Extension Studies Software Engineering Computer Software Engineering, Masters of Liberal Arts Extension Studies Software Engineering Computer Software Engineering at Harvard UniversityBSEE Electrical and Computer Engineering, BSEE Electrical and Computer Engineering at Purdue University
Chinese
Github Skills (7)
decision-tree10
logistic-regression10
machine-learning10
adaboost10
naive-bayes10
python10
numpy9
Programming languages (4)
Github contributions (5)
pbharrin/machinelearninginaction
May 2011 - Feb 2016
Source Code for the book: Machine Learning in Action published by Manning
Role in this project:
ML Engineer
ML EngineerContributions:58 commits, 2 PRs, 1 push in 4 years 10 months
Contributions summary:Peter primarily contributed to the codebase by adding, modifying, and refining code for machine learning algorithms. Specifically, the user added and updated multiple Python files implementing k-Nearest Neighbors (kNN), decision trees, Naive Bayes, Logistic Regression, Support Vector Machines (SVMs), and AdaBoost. These contributions included implementing core functions, adding new datasets, and improving the overall functionality of various machine learning models, providing a comprehensive suite of ML techniques.
pythonmanningdata-sciencemachine-learning-bookmachine-learning
pbharrin/pyconometrics
May 2012 - Oct 2012
Contributions:9 commits in 5 months
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