Amazon Food Reviews, Part II
Ok, so now that we explored the contents of the Amazon Fine Reviews data file, it's time to move on to the second task: How many reviews and products are perfectly positive and
Recent posts
Amazon Food Reviews, Part I
It takes time to take advantage of all the great data science/ML resources out there like Coursera, Udacity, HackerRank, and Kaggle competitions. I won't bore you with the details, but granted that
Analyzing U.S. Veterans Incomes
Using data from the American Community Survey, I analyzed the disparity of male over female veteran and non-veteran median income. Which states have the greatest disparity in income between the sexes? This post
Faker and Feature Importance
I ran into a pretty neat fake name generator that also generates fake addresses in different languages, called Faker: https://pypi.python.org/pypi/Faker. Using Faker, I generated a set of fake
Classifying business documents
In a project two years ago, I wrote a basic Naive Bayes classification script, largely from this tutorial off of scikit-learn's site, which was pretty much all that I needed. I typically use
Off my machine learning bucket list - the MNIST Tensorflow Tutorial
I'm definitely no where close to a deep learning expert. But, I'm pretty curious and interested to learn more about it and how I could start using it for "everyday" business