An end-to-end machine learning example using Pandas and Scikit-Learn
One of the machine learning workshops given to students in the Georgetown Data Science Certificate is to build a classification, regression, or clustering model using one of the UCI Machine Learning Repository datasets. The idea behind the workshop is to ingest data from a website, perform some initial analyses to get a sense for what's . . .
How Not to Lose Friends and Alienate People
If you want to keep a secret, you must also hide it from yourself.
— George Orwell 1984
In order to learn (or teach) data science you need data (surprise!). The best libraries often come with a toy dataset to illustrate examples of how the code works. However, nothing can replace an actual, non-trivial . . .
For the mind does not require filling like a bottle, but rather, like wood, it only requires kindling to create in it an impulse to think independently and an ardent desire for the truth.
— Plutarch On Listening to Lectures
The impulse to ingest more data is our first and most powerful instinct. Born with . . .
Discrete events pervade our daily lives. These include phone calls, online transactions, and heartbeats. Despite the simplicity of discrete event data, it’s hard to visualize many events over a long time period without hiding details about shorter timescales.
The plot below illustrates this problem. It shows the number of website . . .
Sentiment analysis is a common application of Natural Language Processing (NLP) methodologies, particularly classification, whose goal is to extract the emotional content in text. In this way, sentiment analysis can be seen as a method to quantify qualitative data with some sentiment score. While sentiment is largely subjective, sentiment . . .
Hadoop is the standard tool for distributed computing across really large data sets and is the reason why you see "Big Data" on advertisements as you walk through the airport. It has become an operating system for Big Data, providing a rich ecosystem of tools and techniques that allow you to use a large cluster of relatively cheap . . .
Efficient Processing, Schemas, and Serialization
I wanted to write a quick post today about a task that most of us do routinely but often think very little about - loading CSV (comma-separated value) data into Python. This simple action has a variety of obstacles that need to be overcome due to the nature of serialization and data transfer. In fact, I'm routinely surprised how often I . . .