Bob Uva

Two of my favorite podcasts are Clear+Vivid by Alan Alda, and Hanselminutes by Scott Hanselman. Both hosts are excellent communicators. This morning, while walking the dogs, I listened to the last part of Alan's talk with the author/biologist, Thor Hanson. When that episode finished, I went on to

A cheatsheet is like a reference page, with the difference that it provides a quick lookup of the most common features. I really like this pandas cheatsheet for that reason. When I haven't done data-wrangling or cleaning in a while, it helps me to get a quick answer. One other

I'm just starting to get back to data science and glad to have found Hadley Wickham's and Garrett Grolemund's book, R for Data Science. It looks to be a good refresher for me. In reading the Introduction, I'm immediately struck with how helpful this book is going to be. In

From a quick review of measurements of biodiversity that I found on Wikipedia, there appear to be at least a couple of mathematical formulas for calculating it. Yet I don't think of biodiversity in such an abstract way. To me the term relates more to how natural our earth environment

When I get a data set to explore, the first thing I think about is the cleanliness of the data. If it's survey data, there may be inconsistencies in the collection method, especially if the data spans years of surveys. From reading the freely-downloadable textbook, Think Stats, I discovered the

I've been getting back into exercising my data science muscles, and as I do continue, I'd like to put together some interesting blog posts. But I don't want to wait until I've got a full data story together. So I'm going to start blogging shorter learnings in addition to longer

It's been about two years since I started taking the Coursera data science specialization courses. I completed I think six of those courses. I still have the Regression Models, Practical Machine Learning and Developing Data Products courses to complete before doing a Capstone project. I'm not sure if I can

Over the past six to nine months I've been gravitating toward services development in Java. Having worked in .NET/C# for most of the past dozen years, I have had to enable my frustration shielding as I learned not just a new language but mostly a new set of development,

I've finished the R programming course and have now moved on to the next course in the sequence, Getting and Cleaning Data. In this one, I'll have the chance to further practice with R, reading formats, slicing and dicing the data into form, and creating what data scientists call a

The John Hopkins' Coursera course on R Programming started two weeks ago and I thought I'd share some of my thoughts on the course and my growing knowledge of R. The programming assignments in this course are, thankfully, challenging. I was concerned about the exercises being too simple in order

I was able to get in a couple of workouts at the gym while on vacation this week, giving me an opportunity to catch up on some podcast listens. The Cloud of Data podcast didn't have any new shows but I discovered a nice new podcast, Data Skeptic. What I

I had an interesting week in the world of Data Science this week. I started learning some R programming, continued to find new and interesting data science learning resources, and had an interesting coincidence occur relating to data science as practiced at my company. Predictive Analytics and Infer On Tuesday

As I said in my first post on this blog, I want to write about my personal experience learning and figuring out data science. Over the past week I have had a breakthrough in clarity that was fueled in part by watching a colleague discuss data science applications. Early in

Today, I read a little more in the HDInsight eBook and ran a word count MapReduce program on the HDInsight emulator. The really canned approach as presented in the book was not keeping my interest. I've been chomping at the bit to get back to doing some Python as it

As I thought about how I would get started digging into data science this past week, my idea was to lay some groundwork for some playful programming that would allow me to get some data analysis experience with a skill (programming) that I am already comfortable with. Then I received