This article was originally published on ETFTrends.com. Watch a complimentary webinar below to learn more about Apache Spark's MLlib, which makes machine learning scalable and easier with ML pipelines built on top of DataFrames. In MapR Technologies video, you'll get to learn about the following: Review Machine Learning Classification and Random Forests Use Spark SQL and DataFrames to explore real historic flight data Use [...]
To illustrate this point by example, Smith turns to another vehicle: a time machine. "Imagine that someone invents a time machine," he writes. "Does she break the law by using that machine to travel to the past?" Given the legal principle nullum crimen sine lege, or "no crime without law," she doesn't directly break the law by the act of time-traveling itself, since no law today governs time-travel. This is where ethics come in.
From Google's language translation app to autonomous cars, machine learning has become a key ingredient in multiple areas of our lives--but what exactly is it? In the simplest sense, machine learning is a method of computer data analysis that learns from its own experience. Once a machine learning algorithm learns what specific patterns look like, it can apply the knowledge on a vast scale. For example, a fraud detection machine learning algorithm may miss a few false charges initially, but once it identifies the pattern, it can protect against millions of future attacks. Check out this week's episode of Tech-x-planations to learn more about the basics of machine learning.
One of the most stressful parts of traveling happens between heading to the airport and waiting to board your flight, as you start checking to see if your flight is on time. Flights already shows delays, and now we're sharing reasons for those delays and delay predictions too. Using historic flight status data, our machine learning algorithms can predict some delays even when this information isn't available from airlines yet--and delays are only flagged when we're at least 80% confident in the prediction.