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Are All Explainable Models Trustworthy?
Explainable AI or Explainable Data Science is one of the top buzzwords of Data Science at the moment. Models that are explainable are seen as the answer to many of recently recognized problems with machine learning, such as bias or data leaks. ... Read more
2020 Outlook on AutoML Updates & Latest Recent Advances
The field of automated machine learning or AutoML continues to expand with new products and services being announced at a frenetic pace. As a data scientist, I’m motivated to carefully monitor this technology because it could potentially impact my profession especially if these tools open up the field of... Read more
Machine Learning for Time Series Data
Most organizations generate time-series data. The generation of sales data and financial data are primary components of all organizations’ business. This data is a form of time series data. Time series data consists of any data that carries a temporal component with it. Time series data is data that... Read more
Getting Started with H2O using Flow
Data collection is easy. Decision making is hard. Today, we have access to a humungous amount of data, which is only increasing day by day. This is primarily due to the surge in the data collection capabilities and the increased computing power to store this collected data. However, collecting... Read more
Inversion of 2D Remote Sensing Data to 3D Volumetric Models Using Deep Dimensionality Exchange
By Graham Ganssle, PhD, Head of Data Science, Expero Inc. Be sure to check out his upcoming talk at ODSC East 2020 this April 13-17, “Inversion of 2D Remote Sensing Data to 3D Volumetric Models Using Deep Dimensionality Exchange,” there! Many companies are continuously exploring for and monitoring the stability of CO2... Read more
Beginner’s Guide to K-Nearest Neighbors in R: from Zero to Hero
In the world of Machine Learning, I find the K-Nearest Neighbors (KNN) classifier makes the most intuitive sense and easily accessible to beginners even without introducing any math notations. To decide the label of an observation, we look at its neighbors and assign the neighbors’ label to the observation... Read more
Research Note: What Are Natural Experiments? Methods, Approaches, and Applications
I enjoy reading Craig et al. (2017) ‘s review article on Natural Experiments (An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research). In this post, I want to summarize its key points and attach some of my reflections about the development of causal inference. This review article... Read more
A Concrete Application of Topological Data Analysis
Today, I will present a Machine Learning application of Topological Data Analysis (TDA), a rapidly evolving field of data science that makes use of topology to improve data analysis. It is largely inspired by one of my projects. Great! Wait… what is TDA? I will start by briefly recalling the basics... Read more
Not Quite a Perfect Model Stack
In model building, the power of the majority can be a great thing. For those scholars of democracy, this does not refer to Alexis de Tocqueville’s tyranny in the power of majority. I apologize as that is probably a poor pun and may be a bit of a nerdy... Read more
Top 7 Machine Learning Frameworks for 2020
Machine learning is a nightmare without some kind of structure. You can’t build everything from scratch, especially if you’re in a business setting. Even if you want to (and if you do, comment here and tell us about it!), you don’t have time in most cases. You need a... Read more