Data Science - Winder.AI Blog

Industrial insight and articles from Winder.AI, focusing on the topic Data Science

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AI Panel of Experts

Tue Mar 6, 2018, in Data Science, Talk

Join the track speakers and invited guests as they discuss where AI is heading and how it’s affecting software today. Enjoyed fielding questions about #DataScience and #AI today at #QConLondon. Great questions and expert speakers, but SMEs are underrepresented in data science. We need more SMEs speaking! pic.twitter.com/Vasi24z3LY — Phil Winder (@DrPhilWinder) March 6, 2018

101: Why Data Science?

Mon Jan 1, 2018, in Training, Machine Learning, Data Science

What is Data Science? Software Engineering, Maths, Automation, Data A.k.a: Machine Learning, AI, Big Data, etc. It’s current rise in popularity is due to more data and more computing power. For more information: https://winderresearch.com/what-is-data-science/ Examples US Supermarket Giants Target: Optimising Marketing using customer spending data. Walmart: Predicting demand ahead of a natural disaster. Discovery Most projects are “Discovery Projects”.

102: How to do a Data Science Project

Mon Jan 1, 2018, in Training, Machine Learning, Data Science

Problems in Data Science Understanding the problem “the five-whys” Different questions dramatically effect the tools and techniques used to solve the problem. Data Science as a Process More Science than Engineering High risk High reward Difficult Unpredictable By Kenneth Jensen CC BY-SA 3.0, via Wikimedia Commons Impacts of Data Science What is the purpose of the project?

201: Basics and Terminology

Mon Jan 1, 2018, in Training, Machine Learning, Data Science

The ultimate goal First lets discuss what the goal is. What is the goal? The goal is to make a decision or a prediction Based upon what? Information How can we improve the quality of the decision or prediction? The quality of the solution is defined by the certainty represented by the information. Think about this for a moment. It’s a key insight. Think about your projects.

The Meaning of (Artificial) Life: A Prelude to What is Data Science? - GOTO Berlin

Fri Nov 17, 2017, in Data Science, Talk

Abstract The Hitchhiker’s Guide says the meaning of life is 42. Considering that the field of Data Science is going through a period of exponential growth it too could soon find that the meaning of an artificial life is also 42. But if you are not involved on a day-to-day basis, the expansion can seem bewildering. The story of how disparate disciplines have combined to produce Data Science is fascinating.

What is Artificial Intelligence?

Fri Oct 6, 2017, by phil-winder, in Data Science, Talk

If you ask anyone what they think AI is, they’re probably going to talk about sci-fi. Science fiction has been greatly influenced by the field of artificial intelligence, or A.I.

Probably the two most famous books about A.I. are I, Robot, released in 1950 by Isaac Asimov and 2001: A Space Odyssy, released in 1968 by Arthur C. Clarke.

I, Robot introduced the three laws of robotics. 1) A robot must not injure a human being, 2) a robot must obay the orders, except where the orders would conflict with the First Law and 3) a robot must protect its own existance as long as such protection does not conflict with the First or Second Laws.

2001: A Space Odyssey is a story about a psychopathic A.I. called HAL 9000 that intentionally tries to kill the humans on board a space station to save it’s own skin, in a sense.

But the history of AI stems back much further…

The Meaning of (Artificial) Life: A Prelude to What is Data Science? - GOTO Copenhagen

Tue Oct 3, 2017, in Data Science, Talk

Abstract The Hitchhiker’s Guide says the meaning of life is 42. Considering that the field of Data Science is going through a period of exponential growth it too could soon find that the meaning of an artificial life is also 42. But if you are not involved on a day-to-day basis, the expansion can seem bewildering. The story of how disparate disciplines have combined to produce Data Science is fascinating.

What Is Data Science?

Sat Jul 15, 2017, by phil-winder, in Data Science, Workshop

Data Science is an emerging field that is plagued by lurid, often inconsequential reports of success. The press has been all too happy to predict the future demise of the human race.

But sifting through chaff, we do see some genuinely interesting reports of work that affects both bottom-line profit and top-line revenue.

Cloud-Native Data Science: Turning Data-Oriented Business Problems Into Scalable Solutions

Mon Jun 12, 2017, in Cloud Native, Data Science, Talk

Abstract The proliferation of Data Science is largely due to: ubiquitous data, increasing computational power and industry acceptance that solutions are an asset. Data Science applications are no longer a simple dataset on a single laptop. In a recent project, we help develop a novel cloud-native machine learning service. It is unique in that problems are packaged as containers and submitted to the cloud for processing. This enables users to distribute and scale their models easily.