Building a Machine Learning model to Forecast Cycle TimeFor engineering, the ability to accurately estimate how long an issue will take is crucial to properly setting expectations and delivering…Nov 19, 2020Nov 19, 2020
Published inTowards Data ScienceTwo data science hacks to improve your workflowData science is fundamental to Pinpoint’s application. But, like most startups, we are still in the process of building out our data…Nov 19, 2020Nov 19, 2020
MLB Gambling Trends; Focus on the Over/Under and Home-Field AdvantageBefore we jump into the trends and facts, a little bit about the data that was used for this analysis. Regarding the over/under lines and…Sep 11, 20171Sep 11, 20171
Grid Searching in Machine Learning: Quick Explanation and Python ImplementationGrid-searching is the process of scanning the data to configure optimal parameters for a given model. Depending on the type of model…Sep 6, 20173Sep 6, 20173
DBSCAN: What is it? When to Use it? How to use itDBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a popular unsupervised learning method utilized in model building…Sep 5, 20177Sep 5, 20177
Published inTowards Data ScienceBoosting in Machine Learning and the Implementation of XGBoost in PythonAs an extension of my previous article outlining Ensemble Methods, this blog will dive into Boosting and all it entails. In its simplest…Aug 16, 20173Aug 16, 20173
Published inTowards Data ScienceEnsemble Methods in Machine Learning: What are They and Why Use Them?Ensemble Methods, what are they? Ensemble methods is a machine learning technique that combines several base models in order to produce one…Aug 2, 20177Aug 2, 20177
