‫Throughout the practical part of this course you will find that we did mention of ghettos and then to
‫flow in this video.
‫We will try to understand what get us and into law.
‫So let's see.
‫Get us is a deep learning framework that provides a convenient way to define and train almost any kind
‫of deep learning model.
‫Basically get us what's at the model level.
‫It will help you define the model that is how many layers how many layers.
‫What is the added function.
‫What is the optimizer etc..
‫But it does not handle the lower level operations.
‫If you remember in the previous two lectures we learned that while training a neural network we need
‫a lot of differentiation metrics manipulation etc. All these are not done by great us.
‫Instead this low level manipulation and differentiation of data is done by certain specialized and very
‫optimized libraries.
‫Good thing about Gates is that it can vote seamlessly with several such lower level libraries.
‫Currently there are three main backend libraries entered law which is led by Google C indicate which
‫stands for cognitive toolkit and is the alert by Microsoft and T.A. which is the library Miller lab
‫at University of Montreal.
‫Any piece of code written and get us can be done with any of these backend without having to change
‫anything in the code but as of now pencil law is the most widely adopted most scalable and most production
‫ready so we will be using pencil law in this course.
‫Now pencil flow or any other such low level library.
‫These libraries need processing power from our system to do all these data manipulation.
‫This processing power can be provided by either you or you which stands for central processing unit
‫or the graphical processing it.
‫By default we do all CPI based installation of K doesn't enter law but if you are running on a system
‫with n really deep you end a properly configured libraries of any media such as CUDA or c you'd be an
‫n which are for B planning then you can install the DB You based version of data enter low back end
‫and then as well so that's all we need to know about get us intent to flow.
‫No need to be overwhelmed by these domes.
‫No you will see how using get us will define our neural network model and then we will take it us to
‫use pencil flow back in to print the model in the next video.
‫We will learn how to install gave us intensive law in our system.