Hey, guys, in this lecture, I'm going to show you how to set up your development environment so that
you can follow along in these courses.
First, let's talk about operating systems.
The three big ones are Windows, Linux and Mac.
Most but not all of my courses are part of the Deep Learning series.
Eventually, the deep learning models were going to build will become so complex that we will need specialized
libraries like V.A. intensive flow to implement them.
Now, as of today, Viento intensive flow are not officially supported on windows.
So if you are interested in deep learning, you will discover pretty soon that there is not much you
can do without a ton of work.
Even working with non GPU enabled libraries like numpty and matplotlib can be a challenge, but these
are at least possible on windows.
If you really must use windows and have your python environment inside of windows and you don't want
to try the virtual machine method, which I'm going to discuss next, then one good library I know of
is called Anakonda.
You can get Anakonda at Continuum IO downloads.
I can't vouch for this 100 percent because I haven't used it myself, but I've known others who have
found it at least usable.
Now I'm telling you this from experience.
I've worked with a ton of clients one on one, and python development, especially when it involves
the numpties IP stack is not easy when it's on Windows.
The method I'm going to describe using virtual machines will work on most modern computers.
And as of right now, if you want to do any deep learning stuff, whether that be with Fiinal or Tenzer
flow, you cannot do this on windows.
With that out of the way, I'm going to quickly go over which courses I've released so far or plan to
release in the near future that do not require Ficano intensive flow.
So it's possible to do on windows.
With these in mind, you can decide if you want to install a virtual machine or not, but I would highly
recommend it because it's free and everyone can follow the same instructions.
So we've got linear regression in Python, logistic regression in Python, which are the prerequisites
to deep learning Part one, and we have deep learning in Python, part one, which is mostly in dumpy
and a little bit of tensor flow.
We've got easy natural language processing in Python data analytics.
Ask you all for newbies, beginners and marketers, cluster analysis and unsupervised machine learning
in Python and unsupervised machine learning.
Hidden Markov models in Python.
This course is going to have a little bit of piano in it next.
Here are some courses that depend heavily upon piano or tensor flow or both.
We've got practical, deep learning in V.A. intensive, low, convolutional neural networks in Python,
unsupervised, deep learning in Python and recurrent neural networks in Python.
As you can see, a lot of interesting and complex stuff can be done in V.A. intensive flow.
All right.
So hopefully I've convinced you that using a virtual machine is a good idea.
Windows is a great operating system, but it tends to not be as developer friendly since it tries to
be more consumer friendly.
Note that if you're on a Mac, this probably isn't necessary.
You can just install Numpties Sipi Panda's matplotlib, Viento and Tenzer flow using easy install PIP.
Sometimes this stuff can fail, depending on the many combinations of versions of each thing that are
possible, but usually just Googling your error message will lead you to the right solution on stack
overflow.
If you're on a Mac, you can just do pseudo pip install, no Mississipi Python, Pendas, matplotlib
and theno.
Alternatively, you can use easy install, which might have a more recent version.
You may need to use easy install to install PIP itself, which is just too easy and stop it.
If you want to install Tenzer flow, just copy the command at Tancer Vlog.
It's just a PIP install command that points to their custom installation location.
I won't put it here since it corresponds to a specific version and that version may become out of date
by the time you watch this.
That is good news because the people working on Tenzer Flow are updating it all the time.
All right.
So if you've made it this far, that means you want to install a virtual machine with Linux on Windows
or that you're already using Linux and you want to know what commands to use to install these libraries.
We are going to need two things to start for this tutorial, virtual box and a lightweight version of
Ubuntu.
I would recommend Ubuntu or elevon, too.
I'm going to use the 64 bit version of Ubuntu for this tutorial.
So download these first and then return to the tutorial.
All right.
So now that you've got virtual box installed, we're going to create a new machine with 64 bit Ubuntu.
So you want to hit new type in a name for your machine.
And this stuff is already correct.
I'm going to choose a.
Two gigs of memory, you can choose more memory if your computer has more memory.
I'm going to create a virtual hard disk now.
I'm going to choose dynamically allocated and ECGs is good enough for this example.
All right, so I'm going to go to settings if we go to storage.
You can choose.
The ISO file that you downloaded, so I'm going to load up the Ubuntu ISO that you downloaded from everyone
to Whodunnit.
All right.
So OK.
And it start.
So it's going to take you through the installation of everyone to see you want to hit install.
All right, so Element, who is going to take you through some prompts?
All right, so you want to erase this, get install Ubuntu.
And I'm not going to check any of these continue.
All right, so once that's done, it's going to ask you to restart, so just restart now.
All right, now that you're in the machine, what I always like to do, if you notice how this window
is too big for my Mac window, you can make the enter window sizable by installing just additions.
And this also lets you do useful things like cut and paste between machines.
So you want to open a terminal, you go to system tools, select ELEX terminal.
Now I'm going to cry into.
That folder.
Also, the correct command was Ceruti slash Vyborg Linux editions that run.
Notice how there was something that failed in there, so we need to install Jack.
So you want to run Sudo and get UPD?
And then runs through app get upgrade.
So the next thing is you want to sue, to get stall, build essential.
All right, once you've done that, we can try to run Reebok's editions again so that sudo.
Don't slash.
If he barks Lennix.
All right, so everything worked this time, so we're going to restart this machine.
All right, so now the window is only as big as I want to drag it.
OK, so now we can install the actual data science stuff, so you want to open again, Alex Terminal
to a pseudo app to get update again?
And you want to install it's a long list, so Python number, no Python Sibai.
Python, matplotlib, ie, Python, Python, Pip, Python, Dev and Python set up tools.
Yes.
All right, so now that that's installed, you can test it out, can type in Python.
So I python is open, import, vampy.
Numpties working in Port Zippi Import Panda's.
Right, we don't have pandas yet.
We will install our next import matplotlib.
So we have everything we've installed so far.
So now we're going to install
pandas and piano, so that's Pippin's still minus minus upgrade pandas the.
All right, so now we've got Fiorino, the last thing we need is Tenzer flow.
To get this, you guys want to go to the Tenzer Flow website and just grab the latest command since
they're updating the package all the time.
So let's open a browser.
Let's search for install Tenzer flow.
All right, you take this code.
Copy and paste it in here.
All right, now you've got V.A. intensive flow, you can test them out, go to GitHub, dot com slash
lazy programmer slash machine learning examples.
But.
All right, so you need to get if you want to check out this code with get, so let's install it.
All right, so let's run our clone command again.
Let's try the HTTPS version.
OK, so this one works.
All right, so you see into machine learning examples go into an in class, too.
So this has some introductory.
Tenzer flaunt the anecdote, soldiers run Python, V.A. wound up high since this does not require any
data.
Cool.
So it seems everything is working now let's try the Tenzer, for example, so it's Tenzer flow one.
All right, so you want to make sure you install the correct answer flow, you want the CPU only version.
Hopefully it just overrides the other version without any trouble.
So let's try the example again.
Super.
So now everything is working.
Now, if you want, there is a text editor that I highly recommend, it's called Sublime Text.
So you had download.
You go to Bunta 64 bit.
You save this.
And it will automatically be installed.
All right, so now you have the exact same text editor that I use in my lectures.
So you open machine learning examples, and this is all of our code.