Formally $P\left(F\mid E\right)$ is defined by the condition: $$P\left(F\mid E\right)P\left(E\right)=P\left(E\cap F\right)$$
If $P\left(E\right)\neq0$ this comes to the same as $P\left(F\mid E\right)=\frac{P\left(E\cap F\right)}{P\left(E\right)}$.
However if $P\left(E\right)=0$, then, since $(E\cap F) \subset E$, it follows
that $P(E\cap F) \leq P(E)$ and so $P(E\cap F)$ also equals $0$. Thus, the
definition of $P\left(F\mid E\right)$ as a fraction becomes of the form
$\frac{0}{0}$ and cannot be used to decide the value of $P\left(F\mid E\right)$.
Nor does $P(F \mid E)\cdot P(E) = P(E\cap F)$ help because $P(F \mid E)\cdot 0 = 0$ is true for all choices of value for $P(F \mid E)$.
Two events $E$ and $F$ are by
definition independent if: $$P\left(E\cap F\right)=P\left(E\right)P\left(F\right)$$
Note that this is an expression symmetric in $E$ and $F$. Note also that
if either $P(E)$ or $P(F)$ equals $0$, then $P(E\cap F)$ also necessarily
equals $0$ and so $P(E\cap F)=P(E)P(F)$ automatically holds: an event
of probability $0$ is independent of all other events.
Statement "$E$ is (in)dependent of $F$" must be read as: "$E$ and $F$ are (in)dependent".
If $P\left(E\right)\neq0$
then it comes to the same as $P\left(F\mid E\right)=P\left(F\right)$
and if $P\left(F\right)\neq0$ then it comes to the same as $P\left(E\mid F\right)=P\left(E\right)$.
I advice you not to use these conditional expressions as definition of independence.
The special cases $P\left(E\right)=0$ and/or $P\left(F\right)=0$
are somehow spoiling.