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From YouTube: Incubation Engineering MLOps - Update 2023-02-06
Description
Iterating on UX Review, efforts on Incubation foundations, starting closed testing
- Showcase: https://www.youtube.com/watch?v=E8GhtXXm_O0
- Feedback Issue: https://gitlab.com/gitlab-org/gitlab/-/issues/381660
- This Update: https://gitlab.com/gitlab-org/incubation-engineering/mlops/meta/-/issues/67
- All Updates: https://gitlab.com/gitlab-org/incubation-engineering/mlops/meta/-/issues/16
A
Hello,
everyone
and
welcome
to
another
update
for
incubation
engineering
here
at
gitlab.
My
name
is
Eduardo,
and
today,
I'm
gonna
be
talking
a
little
bit
more.
What's
been
done
on
the
past
few
weeks
for
model
experience
tracking,
so
Circle
back.
What
I
want
to
do
is
give
reasons.
Foreign
tracking
is
one
of
these
I'm
implementing
a
backend
for
ammo
flow,
so
that
data
scientists
can
use
their
ml
flow
code
to
record
their
candidates
or
their
runs
into
gitlab
and
make
it
easier
for
them
to
use
external
tracking.
A
So
on
that
right
now,
I
implement
the
the
past
few
weeks.
I
did
Implement
usage
metrics
for
this.
For
this
feature,
so
a
few
metrics
to
just
got
how
much
users
will
start
using
it.
So
number
of
candidates
created
number
of
of
projects
number
of
users
that
created
candidates,
those
kinds
of
stuff,
then
so
these
are
usage,
metrics
and
but
they
just
tells
usage,
not
customer
value.
A
Well,
we
incubation
Engineers.
We
have
a
different
flow
of
work
because
we
are
creating
a
lot
of
stuff
so
and
we
are
starting
to
create
repeat.
We
are
using
repeated
code,
repeated
patterns
and
I
invest
a
little
bit
of
time
into
extracting
a
bit
of
these
patterns
into
components
or
into
usable
functions
so
that
we
can
share
between
between
us.
Additionally,
I
recorded
a
larger
Showcase
of
model
experiment
tracking.
So
it's
a
12
minute
video
that
explains
what
is
model
experiment
tracking.