On my bucket list for this year is a commitment
to do more tinkering with machine learning and AI
and as I've started this research,
I keep running into references to what is a tensor,
what is a tensorflow.
Let's break this down real quick.
TensorFlow is an open source project you can access via GitHub,
and it can be used with a variety of modern languages
like Python, JavaScript, Java and C++.
Put simply it's used to develop and improve AI and machine learning models,
which is why you hear about it so much.
So the second question makes me ask,
What is a "tensor" anyway?
It turns out a tensor is an algorithm
expressed as a multilinear,
which is essentially a complex array used in machine learning.
One way of showing this is a multi dimensional array, kind of like this shape.
TensorFlow is an open source platform for creating and using models is just that simple.
And what I wanted to outline is kind of the way you work through it.
It is a very iterative platform
where you can really get started immediately,
taking advantage of machine learning.
It comes first by doing the training.
Now when it comes to building these models, creating them,
there are many decisions to make,
and this is where TensorFlow really aids in this process.
And you can decided to say,
Hey, I wanted to train this. I have a set of data.
I want to make this model be a CPU, be trained by CPU or GPU,
or there's even tensor computing processing units
that you can do as well to train your data.
But it gives you an opportunity to make that decision when you want to create the model.
Now, if you don't have your own data,
you can, it will give you data sets that you can leverage.
All right.
If you kind of don't want to go the process of
creating your models by hand, there are some starters, let's say,
we call them estimators, which are like starter neural networks
to get started or models that you can use to really try to jump start
your process of doing this.
And then the last part is
once you have something, you have to deploy that.
Well, another great part of that is you can also give you an API
TensorFlow is going to give you an API you can use
code name Keras,
but that will be a way that you can actually input data to train your models.
It encapsulates any of the models that you want to create.
So very important there,
that process of getting started is very easy.
Now, the last part you may say is,
"All right, I'm using TensorFlow."
"I want know what I want to achieve in my application,
but how do I get it into where I want to develop?"
And that's where the last part that it offers for you, it gives you a method for deployment.
A. It's going to let you get into mobile
and embedded, abbreviated EMB.
So iOS, Android SDKs
and the ability to get on Raspberry Pis, all right
Linux arm SDKs for you to get there as well.
Secondly, you'll be able to get on browsers.
There's going to be a library which is TensorFlow JS,
which will give you a mechanism for creating and executing
your models inside your code as well.
And also you can do I kind of mentioned embedded systems,
but that's something you could do.
But there's an additional piece here too.
You could get even get it on embedded devices.
They even have microcontrollers.
So the opportunities are endless here to really get started here.
Well, for me, when I want to get started with something,
I actually love being able to take advantage
of any platform I can that can help me jump start and get going.
And that's what you should do.
I want you to leave in the comments what you think about TensorFlow
and tell us how easy it was to jump start your journey.
As always, Señor España.