Steps to Install TensorFlow Keras

Machine
learning
frameworks
such
as

TensorFlow
and
Keras
have
revolutionized
the
transformation
of
the

artificial
intelligence
landscape.
The
frameworks
help
machine
learning
and

deep
learning
engineers
work
on
new
projects
without
worrying
about
the
technicalities.
Interestingly,
there
is
no
comparison
between
TensorFlow
and
Keras,
as
Keras
works
as
a
wrapper
for
the
TensorFlow
framework.
You
can
install
TensorFlow
Keras
together
and
make
the
most
of
the
two
frameworks.

Keras
is
a
trusted
tool
for
machine
learning
specialists
working
with
Python.
It
works
by
leveraging
schemes
and
models
that
guide
the
distribution
and
transformation
of
data.
Machine
learning
involves
processing
information
through
programmed
data
with
certain
decisions
dependent
on
specific
data.
Let
us
learn
more
about
the
prerequisites
and
important
steps
for
installation
of
Keras
with
TensorFlow.

What
are
the
Prerequisites
for
Installation
of
Keras?

The
best
practices
for
a
TensorFlow
Keras
install
on
your
system
would
focus
first
on
the
prerequisites.
You
would
need
a
server
that
offers
root-level
access.
Another
important
requirement
for
installing
Keras
is
the
installation
of
TensorFlow.
You
can
choose
the
CentOS
7
as
the
preferred
operating
system
for
the
installation
process.

What
are
the
Steps
for
Installing
Keras
with
TensorFlow?

The
answers
to
queries
like
“How
do
I
install
TensorFlow
and
Keras?”
would
guide
you
through
an
organized
process
that
involves
installation
of
the
required
dependencies.
You
have
to
install
Python
and
TensorFlow
before
you
can
install
Keras.

Installation
of
Python

Python
is
an
important
requirement
for
installing
Keras.
The
primary
reason
behind
the
installation
of
Python
is
that
Keras
is
a
Python-based
framework.
You
should
choose
the
most
recent
version
of
Python
for
installation
of
Keras.
Here
is
an
outline
of
the
steps
that
you
must
follow
to
install
Python
3,
the
latest
version
of
Python.

• 
  Updating
  the
  Environment 

You
must
ensure
that
you
have
an
updated
environment
with
all
the
necessary
packages
in
place.
Here
is
the
command
for
updating
the
environment.

[root@centos7 ~]# yum update –y

• 
  Python
  3
  Installation 

After
updating
the
environment,
you
can
install
Python
3
by
using
the
following
command
line.

[root@centos7 ~]# yum install -y python3

Another
alternative
to
the
answer
to
“How
do
I
install
TensorFlow
and
Keras?”
would
involve
using
the
Pip
Python
package
manager.
It
can
help
you
install
the
Python
package
manager
with
the
Python
3
package.

• 
  Verification
  of
  Python
  Installation

Once
you
have
installed
Python
3,
it
is
important
to
ensure
that
the
installation
is
usable
and
stable.
Therefore,
you
can
use
a
Python
3
shell
by
using
a
command
like
the
following.

[root@centos7 ~]# python3 Python 3.6.8 (default, May 30, 2024, 17:28:10)  [GCC 4.8.5 20150623 (Red Hat 4.8.5-39)] on Linux Type "help," "copyright," "credits," or "license" for more information. >>>

The
output
would
show
the
version
of
Python
3
that
you
have
on
your
system.
In
addition,
it
would
also
feature
a
different
type
of
command
prompt
characters.
In
some
cases,
you
can
opt
for
a
source
installation
to
install
the
latest
version
of
Python. 

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Installation
of
TensorFlow

The
next
step
requires
you
to
install
TensorFlow
with
Keras
compatibility
to
move
ahead
with
the
installation
process.
TensorFlow
is
a
formidable
backend
engine
that
serves
as
a
mandatory
prerequisite
for
installation
of
Keras.
Here
are
the
steps
to
install
TensorFlow
on
your
system.

• 
  Set
  Up
  the
  Virtual
  Environment

The
first
step
in
installing
TensorFlow
involves
creation
of
a
virtual
environment.
First
of
all,
you
would
have
to
create
a
folder
with
the
help
of
following
commands.

# mkdir test # cd test

You
can
set
up
the
virtual
environment
by
using
Python.
The
following
command
will
help
you
create
a
virtual
environment
with
the
name
‘tf-virtual-env.’
You
can
replace
the
name
according
to
your
requirements.

# python3 -m venv tf-virtual-env

The
environment
is
an
important
requirement
for
installing
Keras
and
TensorFlow,
as
it
offers
access
to
different
pre-installed
Python
tools
and
libraries.
For
example,
you
can
find
Pip
or
the
Package
installer
for
Python.
Use
the
following
command
to
make
the
virtual
environment
functional.

# source tf-virtual-env/bin/activate

You
will
find
the
following
change
in
the
prompt
if
you
have
an
operational
virtual
environment.

(tf-virtual-env) # _

You
can
type
deactivate
and
press
Enter
at
the
prompt
to
move
out
of
the
virtual
environment.
Remember
that
TensorFlow
installation
needs
a
Pip
19.0
version.
The
following
command
can
help
you
check
the
version
of
Pip
installed
in
your
system.

# pip install --upgrade pip 

• 
  Installation
  of
  TensorFlow

You
can
install
TensorFlow
Keras
without
needing
GPU
support.
The
following
command
can
help
you
install
a
TensorFlow
version
that
does
not
need
GPU
support.

# pip install --upgrade tensorflow

The
same
command
can
help
you
update
TensorFlow.

• 
  Virtual
  Environment
  Testing 

The
final
step
in
installation
of
TensorFlow
involves
testing
the
environment.
You
can
begin
the
virtual
environment
testing
by
opening
Python
bash
using
the
following
command.

# python

The
next
phase
of
this
step
involves
importing
TensorFlow
packages
to
the
Python
interpreter
session
and
printing
the
version
of
TensorFlow
installed
on
your
system.

import tensorflow as tf print(tf.__version__)'

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Installation
of
Keras

The
recent
update
in
TensorFlow
2.0+
removes
a
lot
of
the
TensorFlow
Keras
install
complexities.
You
don’t
have
to
install
Keras
if
you
complete
the
TensorFlow
installation
process
according
to
the
instructions.

You
can
confirm
the
Keras
installation
by
accessing
Python
bash
with
the
following
command

# python

In
the
next
step,
you
have
to
use
the
following
commands
in
the
terminal.

import
keras

keras.__version__

The
following
steps
can
help
users
who
use
TensorFlow
versions
earlier
than
2.0
for
installation
of
Keras
with
the
Pip
package
manager.

• 
  Install
  Keras

You
can
use
the
following
simple
command
to
install
Keras
in
your
system
using
TensorFlow
and
Python.

pip3 install keras 

• 
  Verify
  the
  Installation

Another
simple
command
can
help
you
verify
the
installation
of
Keras.
The
output
of
the
following
command
would
also
display
the
package
information.

pip3 show keras

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Can
you
import
Keras
Libraries
into
the
Keras
TensorFlow
installation?

The
Python
virtual
environment
is
an
important
requirement
for
installing
TensorFlow
with
Keras,
as
it
offers
easier
access
to
the
most
significant
libraries.
The
Python
libraries
can
help
you
work
on
machine
learning
projects
with
access
to
a
broad
range
of
functionalities.
Some
of
the
important
Python
libraries
included
in
the
virtual
environment
include
Numpy,
Scipy,
Pandas,
Matplotlib,
Seaborn,
and
Scikit-learn.

How
Can
You
Update
the
Keras
Installation?

The
flexibility
to
install
Keras
and
TensorFlow
together
offers
a
promising
advantage
as
they
can
update
at
the
same
time.
The
command
to
update
TensorFlow
can
also
help
you
update
the
Keras
installation
on
your
system.

# pip install --upgrade tensorflow

Final
Words 

The
steps
to
install
Keras
on
your
system
with
TensorFlow
provide
an
easy
guide
to
accessing
the
most
powerful

machine
learning
frameworks.
You
can
find
answers
to
queries
like
“How
do
I
install
TensorFlow
and
Keras?”
without
the
need
for
a
virtual
environment.
However,
it
could
lead
to
risks
and
more
complexities
than
the
commands
used
in
pre-configured
environments.

TensorFlow
and
Keras
offer
a
diverse
set
of
functionalities
to
simplify
working
on
machine
learning
projects
with
more
efficiency.
Learn
more
about
TensorFlow
and
Keras
to
explore
their
advantages
and
how
they
work
before
you
install
the
frameworks.
Find
the
best
resources
to
discover
the
capabilities
of
TensorFlow
and
Keras
now.