How I got into data science

In the third year of my PhD, I had a decision to make. Research, especially the academic kind, just wasn't working for me. I was getting results and publications, but knew that it could never be a lifelong career for me. Things moved slowly. I disliked the territorialism and being a master of abstractions, outside… Continue reading How I got into data science

Analyzing resumes with data science

Ever wonder if there is a "secret code" for resumes, some key words that will actually make you stand out? It turns out there are indeed some very characteristic differences between experienced and novice resumes. Gathering Resume Data Resumes from an resume search were used to analyze the differences between experienced and inexperienced resumes. For maximum… Continue reading Analyzing resumes with data science

What I’m reading/watching/taking

Books, videos and courses I've done, am doing or want to do, for the curious and for my own reference. Read/watched/took: Machine Learning with Andrew Ng Biostatistics Boot Camp 1&2 with Brian Caffo - Link to 2 Data Science For Business CS231N with Andrej Karpathy Statistical Rethinking Mathematical Statistics and Data Analysis Introduction to Statistical Learning… Continue reading What I’m reading/watching/taking

Linear Regression vs. Decision Trees: Handling Outliers

In regression tasks, it's often assumed that decision trees are more robust to outliers than linear regression. See this Quora question for a typical example. I believe this is also mentioned in the book "Introduction to Statistical Learning", which may be the source of the notion. Predictions from a decision tree are based on the… Continue reading Linear Regression vs. Decision Trees: Handling Outliers

Lead Scoring with Customer Data Using glmnet in R

Lead Scoring Lead scoring is an important task for business. Lead scoring is identifying which individuals in a population may convert (purchase) if marketed to, or assigning them a probability of converting, or determining how much value that individual may have as a customer. Properly using data to support this task can greatly benefit your… Continue reading Lead Scoring with Customer Data Using glmnet in R

Deep Neural Networks: CS231n & Transfer Learning

Deep learning (also known as neural networks) has become a very powerful technique for dealing with very high dimensional data, i.e. images, audio, and video. As one example, automated image classification has become highly effective. This task consists of putting an image into one of a certain number of classes. Look at the results of… Continue reading Deep Neural Networks: CS231n & Transfer Learning