Prophet: forecasting at scale by Sean J. Taylor and Ben Letham via Facebook Research

Facebook is open sourcing Prophet, a forecasting tool available in Python and R. Forecasting is a data science task that is central to many activities within an organisation. For instance, large organisations like Facebook must engage in capacity planning to efficiently allocate scarce resources and goal setting in order to measure performance relative to a baseline.

This is fascinating.

Inside Facebook's AI Machine by Steven Levy via @backchnnl

This new article by Steven Levy explores the work of Facebook's Applied Machine Learning group and shows how Facebook could not exist without AI.

This was really interesting and was good to read as a user of the system.

SLIDESHOW: 10 top ways IT pros are boosting their careers via @infomgmt

What do IT pros hope to accomplish in their careers in 2017? To find out, job site Spiceworks polled more than 1,000 of members of the Spiceworks Community for their IT career resolutions.

I don't think that there is anything in this slideshow that I disagree with.

Fueling the Gold Rush: The Greatest Public Datasets for AI by Luke de Oliveira via @StartupGrind

Though not at the forefront of the AI hype train, the unsung hero of the AI revolution is data — lots and lots of labelled and annotated data—curated with the elbow grease of great research groups and companies who recognise that the democratisation of data is a necessary step towards accelerating AI....Most people in AI forget that the hardest part of building a new AI solution or product is not the AI or algorithms — it’s the data collection and labelling. Standard datasets can be used as validation or a good starting point for building a more tailored solution.

There is a wealth of data out there and it is a good starting point as long as you are careful and don't rely on data that you cannot guarantee is correct and accurate.

WEBINAR: Open Data Science in the AI Era - 8 March 2017

Wednesday, March 8th, 2017
2PM Central | 3PM Eastern | 12PM Pacific

The vast open data science landscape is full of choices but can be overwhelming to the uninitiated. However, organisations that can distil the landscape to the key players are making giant strides in leveraging the unending innovation — including Artificial Intelligence — to drive new business value.

How can you navigate the landscape to identify the key players and the emerging ones? Can your enterprise harness open source without descending into anarchy? How can you embrace R, Python and their thousands of powerful analytic packages without the accompanying legal risks? How do you see through the legacy vendor FUD and make open source work?

We're here to help—Continuum Analytics EVP Anaconda Business Michele Chambers and Computational Scientist Ian Stokes-Rees will help you embark on your enterprise's journey to Open Data Science in this webinar on March 8th at 2pm CST.

In this webinar, you will learn to:

Navigate the open data science landscape

Champion open data science projects for success in your organization

See a practical AI demonstration for enterprises

Register here

How to determine who will be a good data scientist by Eric Larson via @infomgmt

Skilled technologist have a number of key attributes, including a passion for solving problems and the ability to think ‘strategy first.'

Interesting to read this opinion piece and assess yourself against this list.

Informatica announces industry’s first intelligent healthcare data lake by Kyt Dotson via @SiliconANGLE

Data management solutions and big data company Informatica LLC has announced the debut of the industry’s first intelligent data lake, a repository for raw data, that’s made specifically for healthcare.

Interesting new development which proves how common this approach is becoming.