Now that IEEE Spectrum is into the third year of annually ranking languages, we can start looking at some trends over time. What languages are ascendant? Which are losing traction? And which of the data sources that we use to create our rankings are contributing the most to these shifts?

Confused about the theories underlying machine learning frameworks? Dive deep into the details with these freely available texts.
There are few subjects in computing as fascinating, or intimidating, as machine learning. Let's face it -- you can't master machine learning in a weekend, and at the very least it requires a good grasp of the underlying mathematical principles.

Despite highly respectable numbers, big data is still in the early stages of enterprise acceptance, but that could change soon.

Big data has been a big buzzword for more than a few years already, and it has solid numbers to back that up, including $46 billion in 2016 revenues for vendors of related products and services.

Take a look at the map above. It tells the story of a year's population change in the United States, according to the latest census data. It shows where the population is growing, like the coasts, the Sun Belt and the oil fields of western North Dakota.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data.

There is an interesting post on Quora by Michael Hochster about What is Data Science which talks of two types of Data Scientists: Type A Data Scientists and Type B Data Scientists (emphasis mine)

Data Scientists are people with some mix of coding and statistical skills who work on making data useful in various ways. In my world, there are two main types:

Services like Google Analytics are great for amassing key data to help you make the most of your web efforts, but zeroing in on the parts that matter most can be a time-consuming challenge. On Friday, Google added a new feature to its analytics service that taps AI to surface insights automatically.

How enterprises can engage, retain, and strengthen bonds with their customers.

TDWI research consistently reveals that a major driver for analytics, and especially advanced analytics such as predictive analytics, is to deepen an understanding of customer behavior.