Lynx Roundup, September 8th, 2019

Lynx Roundup, September 8th, 2019

Decision Trees in Neo4j! Implementing a Spectral Clustering algorithm from scratch! Writing better SQL queries!

Matthew Alhonte
Matthew Alhonte
Running Decision Trees in Neo4j
Medical Devices – Artificial Intelligence and Reactions to FDA’s Proposed Oversight
In April of this year, the US Food and Drug Administration (FDA) released a discussion paper, Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML) &
Learning SQL 201: Optimizing Queries, Regardless of Platform
A article laying out the common thought processes needed to do SQL query optimization, regardless of platform. Focuses on many common inefficiencies that can be optimized.
Example of Confusion Matrix in Python
michelp/pygraphblas
GraphBLAS for Python. Contribute to michelp/pygraphblas development by creating an account on GitHub.
Open sourcing TRFL: a library of reinforcement learning building blocks
Today we are open sourcing a new library of useful building blocks for writing reinforcement learning (RL) agents in TensorFlow. Named TRFL (pronounced ‘truffle’), it represents a collection of key algorithmic components that we have used internally for a large number of our most successful agents…
Spectral Clustering Algorithm Implemented From Scratch
Spectral clustering is a popular unsupervised machine learning algorithm which often outperforms other approaches. In addition, spectral clustering is very simple to implement and can be solved…
Roundup

Matthew Alhonte

Supervillain in somebody's action hero movie. Experienced a radioactive freak accident at a young age which rendered him part-snake and strangely adept at Python.