About Brandon Rohrer
Brandon Rohrer is Principal Data Scientist at iRobot, specializing in predictive modeling of complex systems, algorithm design, and general purpose machine learning.
Brandon Rohrer Posts (18)

How to Use Python’s datetime  17 Jun 2019
Python's datetime package is a convenient set of tools for working with dates and times. With just the five tricks that I’m about to show you, you can handle most of your datetime processing needs.

Choosing an Error Function  10 Jun 2019
The error function expresses how much we care about a deviation of a certain size. The choice of error function depends entirely on how our model will be used.

Separating signal from noise  04 Jun 2019
When we are building a model, we are making the assumption that our data has two parts, signal and noise. Signal is the real pattern, the repeatable process that we hope to capture and describe. The noise is everything else that gets in the way of that.

Choosing Between Model Candidates  29 May 2019
Models are useful because they allow us to generalize from one situation to another. When we use a model, we’re working under the assumption that there is some underlying pattern we want to measure, but it has some error on top of it.

EndtoEnd Machine Learning: Making videos from images  23 May 2019
Video is a natural way for us to understand three dimensional and time varying information. Read this short post on how to achieve the creation of videos from still images.

Pandas DataFrame Indexing  29 Apr 2019
The goal of this post is identify a single strategy for pulling data from a DataFrame using the Pandas Python library that is straightforward to interpret and produces reliable results.

How Optimization Works  18 Apr 2019
Optimization problems are naturally described in terms of costs  money, time, resources  rather than benefits. In math it's convenient to make all your problems look the same before you work out a solution, so that you can just solve it the one time.

How to Survive Your Data Science Interview  01 Mar 2018
There are many wonderful things about data science. It’s extreme breadth is not one of them. The title of data scientist means something different at every company

Data Science and the Imposter Syndrome  15 Sep 2017
You are not the only one who wonders how much longer they can get away with pretending to be a data scientist. You are not the only one who has nightmares about being laughed out of your next interview.

How to Get a Data Science Job: A Ridiculously Specific Guide  07 Mar 2017
Job hunting is challenging and sometimes frustrating task and we all experience it in our career. Here we provide a very specific and practical guide to get your dream job in Data Science world.