Welcome to applications of deep neural networks in PyTorch with Washington University. Okay, this is the second part of module two. We're going to begin looking at the Python programming language. This is just a quick overview of the Python programming language if you haven't maybe done it in a while and need to see some of the aspects of it that we make use of in this course. We'll continue with the same introduction in parts three, four, and five. I'm going to go ahead and open this in Colab, and the link to this notebook is in the description. Now we can actually run some of the code if we need to. This first part at the beginning is really just to detect if Colab is present or not. I set this variable so that if I do need to take a specific programming route later based on if we're in Colab or not in Colab, I can do that. The Python programming language has been around since for a while. I forget the exact date that it was released. I started dealing with it really in about 2008 when Python 3.

came out, but I'm sure Python 2 was out much longer, and I'm not even sure what Python 1 actually was. I don't think that received widespread use outside. So, here is Hello World. These are code cells. These other cells in Jupyter are text cells or markdown, and you can put in a variety of formatting. That's how I format the entire book for this course. You can run these blocks, and yeah, I know it was not authored by Google. I trust myself actually more than Google. So, you run it, and it will print out Hello World. Now, right now, it's spinning up an entire virtual machine for you with a GPU if you requested one. And by the way, if you want GPUs, you do change runtime type. I'm not using a hardware accelerator because this part doesn't really make use of one, so I'm trying to be efficient. And those are your options there. I do have, although the ones that need a GPU already with that setting set, so it should automatically give you one or not give you one based on if needed. You can

do single line comments like this pound sign in front hashtag lets you put something in as a comment. You can do multi-line strings which is kind of cool. Single or double quotes around something specifies a string. Three quotes you can literally put carriage return line feed these kind of things and it will format it. If you do just single tick it still does exactly the same thing. I tend to put double quotes around strings that are describing things like words that you would find in the dictionary. If it's more cody kind of stuff where I have to put a code in then I'm going to do single quotes. So this sort of hello world there I would not normally use a single tick but to python it all means the same. You can print out numbers 42 42.5 and it will print those out. If you don't put a decimal place behind something it's an integer. Otherwise it's a floating point and that becomes important sometimes. You don't declare your types in python. It's dynamic. It senses what type of type you're going to

have and that can sometimes sometimes cause issues because if something's a string and you don't realize it. If you have two strings that are to the number one and you add them together, it's going to be 11, not two like you might normally had expected. These are integers, integer 10, that's a string, and we can print them out. Older versions of Python would allow you to skip the parentheses, and you'd do that. Don't do that. That's not been allowed since Python 2. That just creates all kinds of inconsistencies. If you have every function in all of Python needs parentheses except for print because it used to be special. Now it's not special. You can do math like you would usually expect. A equals A plus one. If you're used to C++, you can't do this kind of stuff. You can do this plus equals one, and you can print. You can also do interpolated strings. That's that f in front of it, also called f-strings, and you can use single or double.

quotes there, whichever one you prefer. Normally, I probably would have done a double quote there. I'm not sure quite why I chose single quote. And now, it's going to execute the Python code that is right in there with that 'a', and it'll print out the value of 'a' is 10. You don't have to put just variables; you can put code in there, so 'a' plus 5, and it's going to print out 15. You have a lot of ways you can print out numbers, and the f-string, the interpolated string, is the preferred one for this course. They all result in 'a' is 5, though. You can do string arithmetic; you can use format; you can use the percent. If statements are very important, and then this starts to demonstrate how you scope things in Python. Here, we say 'a' equals 5. If 'a' is greater than 5, colon, and notice we indent here; that means it's going to do this line. Else, colon, those colons are important; don't forget them. We'll do this one if you took out

the indent. It's not going to work. You can choose tabs. You can use spaces. Don't use both. You'll get unexpected behavior. Not unless you really like frustration. But pick one or the other. This is one of the most hated features often of Python when people from Java or curly brace languages come and they see, Oh my gosh, you. I could just mess up the white space. Or, What happens if I have a tab there and then I do a few spaces there? What's going to happen? I suggest not finding out. Stay consistent. Use tabs. Use the same number of tabs so you can do multi-layers. And this is where this gets complicated, especially when you are copying and pasting code. Of course, you never copy and paste in programming, right? Just kidding. Stack Overflow is heavily encouraged in this course. So here, we're going to have multi-layer. So a equals five, b equals six. If a double equals five, print The variable a is five. If b equals six, print The variable b is also six. And we also print

out here. So here, there's a lot of layers going on. A is equal to five, so it's going to execute this, and then it's gonna execute this one because it was in here, and it's gonna skip the entire else part. Else means no comparison. L if is when you want to chain a bunch of if statements together. You can also loop through a fixed range. So here, we're going to loop from one to two, that is, from one to three, not inclusive of three. So you just use range for x in whatever you want, one comma a thousand, and it'll count all the way up to nine hundred and ninety-nine. You might see x range somewhere. If you see x range, don't use it, just drop the x. That's Python 2. And here, we're looping from 1 to 3, and we're adding up and accumulating, and we print each step, and then we print the final accumulation. Thank you for watching this video, and if you want to follow along with the course, please subscribe to my YouTube channel.

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Introduction to Python for PyTorch Deep Learning (1.2)

Introduction to Python for PyTorch Deep Learning (1.2)

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