Monday, September 23, 2019

Machine Learning Decision Tree w Bagging Implementation

https://docs.google.com/document/d/1dw_kCWJv_WjaM9C-3Hvuna2rREuLzHWOajnhppyGpp0/edit?usp=sharing

This week I've implemented a decision tree algorithm that splits upon correlation creates a regressor based upon an input set of training data. I've also implemented bagging that uses randomized datasets with replacement to smooth out potential overfitting problems over many trees.

Monday, September 9, 2019

Machine Learning Stock Portfolio Optimization in Python





This week in Machine Learning for Trading I've implemented an optimizer using SciPy that takes any number of stock symbols and most effectively allocates one's portfolio among the provided options based upon previous data in a given date range. The metric for evaluating the profitability of a portfolio is based upon the Sharpe Ratio, which adjusts a stock's income against its risk.

What is the Sharpe ratio and how is it used? | IG AU

This work correlates to work I'd done using optimizers to find the optimal behavior for a multi-agent system in the Reinforcement Learning class.

Wednesday, August 28, 2019

Machine Learning Water Turret Pest Deterrent

Here are some pictures of the 3D printed turret I've been working on. It can identify and track targets by adjusting the servos and then activate a water jet by using the solenoid valve controller. It uses Tensorflow using ImageNet custom compiled for Raspberry Pi 3B+. The hull was printed with a hand-constructed Anet A6 3D printer. The hull was designed in FreeCAD. More soon!

Sunday, July 28, 2019