Honest thinking about technology decisions.

An overview of using Prophet for forecasting time series data with a link to jupyter notebooks.

I do love technology, but not as much as I love solving the real problem(s) that my clients have rather than just covering those problems up with band-aids.

In this article, I provide a few tips to make a bit more realistic and useful visualizations from Facebook's Prophet for forecasting time-series library.

Visualizing data is vital to analyzing data. If you can't see your data - and see it in multiple ways - you'll have a hard time analyzing that data

Forecasting time-series data with Prophet. Prophet is a fairly new library for python and R to help with forecasting time-series data.

Doing data science without 'science' is nothing more than throwing darts at a dart board and thinking the results are meaningful.

This is a guest post from Christine Sato Proper risk management is vital to any project manager. Any big project is sure to have a great deal of risk,

This is a multi-bracket, slow shutter capture of Cascade Creek near Durango CO. Captured with Canon 5DsR and Canon 16-35 f/4 L.

A 'rockstar' on paper means little of that person isn't able or willing to get the job done.

A few days ago, I published Collecting / Storing Tweets with Python and MongoDB. In that post, I describe the steps needed to collect and store tweets

Collecting / Storing Tweets with Python and MongoDB provides a script that can be used to collect and store tweets using python and mongoDB

A capture of some of the rapids in Cascade Creek. Captured Canon 5DsR, Canon 16-35 f/4 L.

I use jupyter with vagrant to do 99.% of all my python development. This post explains how easy it is to set up jupyter with vagrant.

Stockstats currently has about 26 stats and stock market indicators included. Definitely not as robust as TA-Lib, but it does have the basics.

If you'e looking for a good, short introduction to Random Forests, check out Machine Learning With Random Forests And Decision Trees.