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 # Small O Notation
 
-Small o notation, denoted as o(g(n)), defines an upper bound on the growth of a function f(n) that is *not* asymptotically tight. In simpler terms, f(n) is o(g(n)) if, for any positive constant c, there exists a value n₀ such that f(n) is strictly less than c*g(n) for all n greater than n₀. This means that g(n) grows strictly faster than f(n) as n approaches infinity.
+Small o notation, denoted as o(g(n)), defines an upper bound on the growth of a function f(n) that is _not_ asymptotically tight. In simpler terms, f(n) is o(g(n)) if, for any positive constant c, there exists a value n₀ such that f(n) is strictly less than c\*g(n) for all n greater than n₀. This means that g(n) grows strictly faster than f(n) as n approaches infinity.
 
 Visit the following resources to learn more:
 

src/data/roadmaps/computer-science/content/small-omega@dUBRG_5aUYlICsjPbRlTf.md

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 # Small Omega
 
-Small Omega (ω) notation is used to describe a lower bound on the growth rate of a function. Specifically, it indicates that a function *g(n)* grows strictly slower than another function *f(n)* as *n* approaches infinity. This means that for any constant *c > 0*, there exists a value *n₀* such that *g(n) < c*f(n)* for all *n > n₀*. In simpler terms, *f(n)* is a strict lower bound for *g(n)*.
+Small Omega (ω) notation is used to describe a lower bound on the growth rate of a function. Specifically, it indicates that a function _g(n)_ grows strictly slower than another function _f(n)_ as _n_ approaches infinity. This means that for any constant _c > 0_, there exists a value _n₀_ such that _g(n) < c_f(n)\* for all _n > n₀_. In simpler terms, _f(n)_ is a strict lower bound for _g(n)_.
 
 Visit the following resources to learn more: