Deep Learning - TensorFlow's Hello World Video Lecture - Tensorflow Learning

hello and welcome in this video we will
provide an overview of the tensorflow
library as well as the structure of a
basic tensorflow application tensorflow
is an open source library for creating
large-scale machine learning
applications it can model computations
on a wide variety of hardware ranging
from android devices to heterogeneous
multi-gpu systems tensorflow uses a
special structure in order to execute
code on different devices like CPUs and
GPUs computations are defined as a graph
and each graph is made up of operations
also known as ops so whenever we work
with tensorflow we define the series of
operations in a graph to run these
operations we need to launch the graph
into a session the session translates
the operations and passes them to a
device for execution to use tensorflow
we need to import the library we'll give
it the name TF so that we can access a
module by writing TF dot and then the
modules name to create our first graph
will start by using source operations
which do not require any input these
source operations or source Ops will
pass their information to other
operations which will actually run
computations let's create two source
operations that will output numbers will
find them is A and B which you can see
in the following piece of code we'll also
define a simple computational operation
TF dot add is used to sum two elements
you could also use C equals A plus B
since graphs need to be executed in the
context of a session we need to create a
session object to watch the graph let's
run the session to get the result from
the previously defined see operation the
following command closes the session in
order to release resources to avoid
having to close the sessions every time
we can define them in a with block after
running the with block the session will
close automatically
you're probably thinking that was a lot
of work just to add two numbers together
but it's extremely important that you
understand the basic structure of
tensorflow because once you do you can
define any computations that you want
and again tensorflow structure allows it
to handle computations on different
devices and even in clusters if you want
to learn more about this you can run the
method TF dot device feel free to
experiment with the structure of
tensorflow in order to get a better idea
of how it works if you want a list of
all the mathematical operations that
tensorflow supports you can check out
the documentation by now you should
understand the structure of tensorflow
and how to create a basic application
thank you for watching this video to
practice and learn more go to the lab
and run the code for yourself