LT2, William Gates Building
Lab Session One 2024-11-05 (Review and Refresher) Practical 1: 2024-11-07 Access
Practical 2: 2024-11-12 Access and Assess (also hand in Practical 1 & Practical One Check)
Practical 3: 2024-11-19 Assess and Address (also hand in Practical 2 & Check) Practical 4: 2024-11-21 Address (also hand in Practical 3 & Check)
There are three types of lies: lies, damned lies and statistics
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There are three types of lies: lies, damned lies and statistics
Arthur Balfour 1848-1930
There are three types of lies: lies, damned lies and statistics
Arthur Balfour 1848-1930
There are three types of lies: lies, damned lies and ‘big data’
Neil Lawrence 1972-?
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bits/min
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billions
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2000
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6
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billion
calculations/s |
~100
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a billion
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a billion
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embodiment
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20 minutes
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5 billion years
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15 trillion years
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More generally, a data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human. She spends a lot of time in the process of collecting, cleaning, and munging data, because data is never clean. This process requires persistence, statistics, and software engineering skills—skills that are also necessary for understanding biases in the data, and for debugging logging output from code.
Cathy O’Neil and Rachel Strutt from O’Neill and Schutt (2013)
We don’t know what science we’ll want to do in five years’ time, but we won’t want slower experiments, we won’t want more expensive experiments and we won’t want a narrower selection of experiments.
Cohen’s kappa inter-annotation used to measure annotator agreement.
pandas
, probability and
correlation)pandas
, setting up SQL on AWS,
uploading data and performing joins with SQL).Chapter 5 of Lawrence (2024)
Chapter 1 of Lawrence (2024)
Chapter 1 of Lawrence (2024)
Chapter 8 of Lawrence (2024)
book: The Atomic Human
twitter: @lawrennd
The Atomic Human pages Le Scaphandre et le papillon (The Diving Bell and the Butterfly) 10–12 , Bauby, Jean Dominique 9–11, 18, 90, 99-101, 133, 186, 212–218, 234, 240, 251–257, 318, 368–369, Shannon, Claude 10, 30, 61, 74, 98, 126, 134, 140, 143, 149, 260, 264, 269, 277, 315, 358, 363, psychological representation 326–329, 344–345, 353, 361, 367, human-analogue machine (HAMs) 343-347, 359-359, 365-368.
podcast: The Talking Machines
newspaper: Guardian Profile Page
blog posts: