by GCBC Ventures | Nov 4, 2021 | Finance, Machine Learning

Introduction We use the K-means algorithm to answer two questions regarding portfolio diversification. How diversified is a given portfolio? How can a diversified portfolio be constructed? Additionally, we use the multidimensional scaling (MDS) algorithm to visualize...
by GCBC Ventures | Apr 3, 2020 | Machine Learning

GPyOpt Python Package Using GPyOpt Best Result and Ensembling Results Code 1. GPyOpt Python Package GPyOpt is a Python open-source library for Bayesian Optimization developed by the Machine Learning group of the University of Sheffield. It is based on GPy, a Python...
by GCBC Ventures | Feb 17, 2020 | Machine Learning

Introduction Optuna References Using Optuna With Sci-kit Learn Results Code 1. Introduction Optuna is a Python package for general function optimization. It also has specialized coding to integrate it with many popular machine learning packages to allow the use of...
by GCBC Ventures | Feb 4, 2020 | Machine Learning

Bayesian Optimization Python Package Using Bayesian Optimization Ensembling Results Remarks Code 1. Bayesian Optimization Python Package Bayesian Optimization (BO) is a lightweight Python package for finding the parameters of an arbitrary function to maximize a given...
by GCBC Ventures | Oct 6, 2019 | Baseball, Machine Learning

Introduction Load Data Build Pipelines Test Results Analyze 2019 Data 1. Introduction In this article, we will use various preprocessors and machine learning algorithms from scikit-learn, along with the scikit-learn wrapper for XGBoost. We determine which...