Difference between revisions of "DataScience"

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'''What would a course on Data Science look like?'''
 
'''What would a course on Data Science look like?'''
  
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[[Media:intro-to-data-science-nov15.pdf|Intro to Data Science]]
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<!--
 
=Introduction=
 
=Introduction=
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[[Image:Data_Science_VD.png|400px|thumbnail|center|Drew Conway's Venn diagram of data science]]
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=Topics would include=
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* What is relevant for the UoB?
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* y=f(x) relationships:- classifiers & regression
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** Examples: Linear & logistic regression, K-Nearest Neighbours, Decision Trees, Neural Networks etc.
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* Data topics:
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** Training, Test & validation data.
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** Sources of data, e.g. web scraping.
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** Exploratory Data Analysis (EDA).
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** Cleaning & munging data (90% of your effort?).  Useful Linux tools.
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** Feature selection.
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* Model selection & training topics:
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** Algorithms that scale.
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** Supervised vs. Unsupervised training.
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** Overfitting.
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** The curse of dimensionality.
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* Programming Skills:
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** "Clean code shows clarity of mind,"
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** Languages: R? Python? Others?
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** Version control.
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** Build systems.
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** Testing.
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** Scripting and automation.
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Latest revision as of 10:45, 5 November 2015

What would a course on Data Science look like?


Intro to Data Science