Overfitting / Underfitting – How Well Does Your Model Fit?

  Supervised machine learning is inferring a function which will map input variables to an output variable. Let’s unpack this definition a bit with an example. Say that we are a bank that wants to determine to whom we should give a loan. The objective, therefore, is to infer a function that examines a set … Continue reading Overfitting / Underfitting – How Well Does Your Model Fit?

Open Data Science

Everyone is talking about data science. One study found that 96% of companies believe that data science is integral to the success of their business. Yet, most of these organizations (70%) are not realizing its full potential. They cite such factors as poor data quality, lack of talent, and access to proper tools and technology[1]. … Continue reading Open Data Science

What is the Philosophy of Data Science (and Should Data Scientists Care)?

Recently I had read a LinkedIn article by Kalyan Sambhangi in which he asked where are all the data philosophers.[1] He makes a good point, if data science is truly a science shouldn’t the philosophy of science be applicable to it as well; i.e. the philosophy of data science. I agree; it should. So, let … Continue reading What is the Philosophy of Data Science (and Should Data Scientists Care)?