Data Science

Reeks: The MIT Press Essential Knowledge series

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  • A
  • concise
  • introduction
  • to
  • the
  • emerging
  • field
  • of
  • data
  • science,
  • explaining
  • its
  • evolution,
  • relation
  • to
  • machine
  • learning,
  • current
  • uses,
  • data
  • infrastructure
  • issues,
  • and
  • ethical
  • challenges.The
  • goal
  • of
  • data
  • science
  • is
  • to
  • improve
  • decision
  • making
  • through
  • the
  • analysis
  • of
  • data.
  • Today
  • data
  • science
  • determines
  • the
  • ads
  • we
  • see
  • online,
  • the
  • books
  • and
  • movies
  • that
  • are
  • recommended
  • to
  • us
  • online,
  • which
  • emails
  • are
  • filtered
  • into
  • our
  • spam
  • folders,
  • and
  • even
  • how
  • much
  • we
  • pay
  • for
  • health
  • insurance.
  • This
  • volume
  • in
  • the
  • MIT
  • Press
  • Essential
  • Knowledge
  • series
  • offers
  • a
  • concise
  • introduction
  • to
  • the
  • emerging
  • field
  • of
  • data
  • science,
  • explaining
  • its
  • evolution,
  • current
  • uses,
  • data
  • infrastructure
  • issues,
  • and
  • ethical
  • challenges.It
  • has
  • never
  • been
  • easier
  • for
  • organizations
  • to
  • gather,
  • store,
  • and
  • process
  • data.
  • Use
  • of
  • data
  • science
  • is
  • driven
  • by
  • the
  • rise
  • of
  • big
  • data
  • and
  • social
  • media,
  • the
  • development
  • of
  • high-performance
  • computing,
  • and
  • the
  • emergence
  • of
  • such
  • powerful
  • methods
  • for
  • data
  • analysis
  • and
  • modeling
  • as
  • deep
  • learning.
  • Data
  • science
  • encompasses
  • a
  • set
  • of
  • principles,
  • problem
  • definitions,
  • algorithms,
  • and
  • processes
  • for
  • extracting
  • non-obvious
  • and
  • useful
  • patterns
  • from
  • large
  • datasets.
  • It
  • is
  • closely
  • related
  • to
  • the
  • fields
  • of
  • data
  • mining
  • and
  • machine
  • learning,
  • but
  • broader
  • in
  • scope.
  • This
  • book
  • offers
  • a
  • brief
  • history
  • of
  • the
  • field,
  • introduces
  • fundamental
  • data
  • concepts,
  • and
  • describes
  • the
  • stages
  • in
  • a
  • data
  • science
  • project.
  • It
  • considers
  • data
  • infrastructure
  • and
  • the
  • challenges
  • posed
  • by
  • integrating
  • data
  • from
  • multiple
  • sources,
  • introduces
  • the
  • basics
  • of
  • machine
  • learning,
  • and
  • discusses
  • how
  • to
  • link
  • machine
  • learning
  • expertise
  • with
  • real-world
  • problems.
  • The
  • book
  • also
  • reviews
  • ethical
  • and
  • legal
  • issues,
  • developments
  • in
  • data
  • regulation,
  • and
  • computational
  • approaches
  • to
  • preserving
  • privacy.
  • Finally,
  • it
  • considers
  • the
  • future
  • impact
  • of
  • data
  • science
  • and
  • offers
  • principles
  • for
  • success
  • in
  • data
  • science projects.
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