The Data Science Venn Diagram by Drew Conway

What is Data Science?

Data Science is a surprisingly hard definition to nail down, especially given the fact that how ubiquitous the term has become.

Vocal critics have variously dismissed the term as a superfluous label (after all, what science doesn’t involve data?)But, these critiques miss something important.

Data science, is perhaps the best label we have for the cross-disciplinary set of skills that are becoming increasingly important in many applications across industry and academia. This cross-disciplinary piece is the key.

In VanderPlas’s opinion, the best existing definition of data science is illustrated by Drew Conway’s Data Science Venn Diagram (see the figure below), first published on Drew Conway’s blog in September 2010.

The Data Science Venn Diagram above captures the essence of what people mean when they say “data science”:

it is fundamentally an interdisciplinary subject. Data science comprises three distinct and overlapping areas:

the skills of a statistician who knows how to model and summarize (big) datasets;

the skills of a computer scientist who can design and use algorithms to efficiently store, process, and visualize this data; and

the domain expertise — what we might think of as “classical” training in a subject — necessary both to formulate the right questions and to put their answers in context.

With this in mind, it would be better to think of data science not as a new domain of knowledge to learn, but as a new set of skills that you can apply within your current area of expertise.

(If you want to get started with your data science journey and apply it in your area of expertise, check out this page for some useful resources that I have collected for you.)

References and Further Reading List:

 

 

Watch Now: Deep Learning Demystified – by NVIDIA

Watch Now: Deep Learning Demystified  (YouTubeUploaded on Mar 30, 2017) 

Artificial Intelligence (AI) is solving problems that seemed well beyond our reach just a few years back. Using deep learning, the fastest growing segment of AI, computers are now able to learn and recognize patterns from data that were considered too complex for expert written software. Today, deep learning is transforming every industry, including automotive, healthcare, retail and financial services.
This introduction to deep learning will explore key fundamentals and opportunities, as well as current challenges and how to address them.
Highlights include:
  1. Demystifying Artificial Intelligence, Machine Learning and Deep Learning
  2. Key challenges organizations face in adopting this new approach
  3. How GPU deep learning and software, along with training resources, can deliver breakthrough results

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WILL RAMEY
Director, Developer Marketing, NVIDIA
Will Ramey is NVIDIA’s director of developer marketing. Prior to joining NVIDIA in 2003, he managed an independent game studio and developed advanced technology for the entertainment industry as a product manager and software engineer. He holds a BA in computer science from Willamette University and completed the Japan Studies Program at Tokyo International University. Outside of work, Will learns something new every day, usually from his two kids. He enjoys hiking, camping, open water swimming, and playing The Game.
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======Below are some main screenshots from the video: