There is a plethora of classification algorithms available to people who have a bit of coding experience and a set of data. A common machine learning method is the random forest, which is a good place to start.
You are a consultant who has been hired by a business that sells one commodity product. On December 31st the price is $100 per unit. The business owner wants to know what to expect by the end of January.
Your client gave you the message:
Prices are based off the the sales the previous day
Roughly 95% of the time, the price will be +/- $10 compared to the day before
With only a few minutes to make the call, how would you decide on what to expect for the end of January? Continue reading →
This post is dedicated to my mother – Seinfeld’s greatest fan.
Seinfeld is a classic TV sitcom. It featured four main characters surrounded by relatively normal, everyday, run of the mill scenarios. In the spirit of Seinfeld, this post will also “be about nothing.” Continue reading →
Continuing ourExplorationof the Data
After identifying the sources of crime growth, it’s time to investigate specific crime rates. This blog post addresses drug and alcohol crimes in Denver over the past few years.
This is a very simplistic view because it will only focus on trend data, which never tells the whole story. Continue reading →