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Hello guys.

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So welcome to the Python series.

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Uh, now we are going to start our first session with respect to Python.

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Now, what we are going to do in this video is that, uh, uh, and the entire code that I'm actually

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going to specifically write, I'm going to use the VS code ID, uh, vs code ID.

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I find it really amazing because here you'll be able to execute your Jupyter notebook files, your.py

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files.

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Along with that, you'll also be able to create all the environments very much easily.

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Uh, so it is feasible that I specifically use VS code.

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Along with that, you have a lot of features like extensions, code assistance, and many more things.

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So the first step, uh, as we have seen starting, you know, uh, what I'm actually going to do is

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that over here, we are going to create our new environment, as I said, um, in this Python series,

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I'm going to use the newest Python version that is Python 3.12, and I am going to teach in such a way

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that we all, we see all the new features that have actually come from 3.10 to 3.12.

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So all the new features that are specifically there, uh, we will be also discussing about them in

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this Python series.

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Uh, the first step, as you know, that, uh, I'm going to create an environment and again, why you

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specifically require an environment because, uh, an environment is, necessary whenever you start

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a new project.

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Because in our Python project or in our data science project, we make sure that we use multiple packages,

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multiple libraries and.

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All right.

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And uh, every couple of months this packages or this libraries have new features and most of them are

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open source packages or libraries.

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Right.

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So they definitely have a lot of features that gets included every couple of months.

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So it is always necessary that you always maintain, uh, or try to create your entire projects in a

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separate, uh, with a separate environment so that there should be not any conflict, as you probably

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go ahead, uh, whenever a new feature is probably coming up, you know, with respect to the packages,

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uh, you can actually create a new project and create a new environment out there.

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But here, uh, the first step, what I'm actually going to do is that let's go ahead and create our

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environment.

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And for this also I will be using conda command.

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So first of all I'll not go ahead and write in PowerShell.

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Instead I'll go and click on uh Command prompt.

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So quickly let's go ahead and write it down.

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So here I'm going to write conda create minus p v and v python uh double equal to.

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Let's say I want to go ahead with Python 3.12 okay.

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And uh understand one thing is that, uh, over here we are using this conda create command v, and

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v is specifically your environment name.

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And which Python version we are specifically using.

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It is 3.12.

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Again based on different different projects.

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It is not necessary that you always need to use 3.12.

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It depends on the kind of packages that are available, let's say open source packages.

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When we are creating deep learning projects or any machine learning projects as such.

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Right.

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So but here, uh, since we are learning this Python series completely from basics, I'm going to go

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ahead and use this environment.

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So once I probably click this.

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So here you'll be able to see the installation will start taking place.

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And when we are creating a virtual environment, some basic libraries or packages will be automatically

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downloaded by this conda command.

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So now here uh you can see over here what are the basic commands, uh, basic new packages that are

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basically getting installed.

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So here are all the packages.

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So I'm just going to go ahead and click on uh press Y.

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And once I probably do this all the installation of the libraries will happen.

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Right.

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So it is going to take some amount of time.

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Again it depends on your internet speed.

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But let me just go ahead and show you.

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So here you can see a V and V environment is basically created.

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And these are all the default packages that you will be able to find out.

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Inside this right there will be a DLL folder.

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There will be an include folder.

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Right.

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So, uh, what is the basic environment that is required for any Python project.

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So that will be covered up inside this particular folder.

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Okay.

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Now once you go ahead and click this uh now the next thing is that let's say um, you, you want to

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activate this environment, right?

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So in order to activate this environment I will go ahead and write conda activate.

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And we go ahead and use this v and v folder itself.

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Write the same v and v folder.

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And here we are just going to give the location of this write.

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So once we press this you'll be able to see that I have activated the V and V environment okay.

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And now you can probably run any kind of.py files directly from here by using Python specifically,

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let's say I probably go ahead and create my app.py.

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And let's say that I am just going to write over here print one plus one.

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Right.

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So this is the basic command.

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Uh, and I'm printing this particular numerical operation one plus one.

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Now if I really want to run this app dot pi, I have to make sure that I'm in the same folder location.

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I have activated my venv environment.

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And now within this particular environment, we will go ahead and just execute this file.

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In order to execute it, you just need to write Python app.py.

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So once you do this here, you'll be able to see that I'm able to get the response.

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Okay.

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Now uh, let me show you one more thing because see uh, as we go ahead with more lectures.

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Right.

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I'm actually going to create a folder, let's say this is first folder is Python basics okay.

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Python basics.

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So inside this folder itself I will go ahead and create my Jupyter notebook file or.py file.

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Anything that I require.

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Let's say I go ahead and create my Jupyter notebook file.

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By default, uh, let's say this is my test dot ipynb.

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Okay.

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Now this Jupyter notebook file, uh, will be the similar Jupyter notebook file that we actually use

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in, uh, Anaconda.

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Right.

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Uh, the Jupyter notebook, but in Python also, uh, sorry, in VS code, you will be able to see that.

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Yes, internally you will be able to execute this text, uh, this uh, Jupyter notebook file also.

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Now, initially, if I go ahead and uh, let's say over here, an option is probably coming up saying

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that, hey, detecting kernels.

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So if I want to say select the same environment right V and V I can go ahead and click on Detect kernels.

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So here you'll get an option of selecting the Python environment.

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Let's say this is the environment that I have created right.

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Uh v and v Python 3.12.0.

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And these are all the other environments that I have actually created in my, uh, local system.

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Right.

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So I'm just going to go ahead and select uh, 3.12.

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Oh okay.

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Now let's go ahead and execute any code.

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Right.

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So this is my code cell okay I can create any number of code cell that I really want right now.

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Code cell is nothing.

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But here I will be writing all my Python code in order to execute it.

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Along with that you also have something like markdown.

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So let's say that I, uh I have this markdown cell.

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I can basically write comments saying like this, like let's say Python example.

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And if I execute it, in order to execute this cell I have to press shift enter.

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Okay.

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So if I probably press shift enter automatically this will get executed.

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Now the the reason we have used some markdown because I needed to write some information over here.

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So like title and all.

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So I'm writing it over here.

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Right.

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So if you press shift enter then automatically this cell will get executed.

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Uh, along with this you also have an option of run all you know, if you want to run all the cells

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over here, if you go ahead and, uh, see if you just go, go ahead and press right click, you'll

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be having so many different, different options.

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Okay.

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But we are just going to use shift run uh shift enter so that we'll be able to execute it okay.

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Now this is fine.

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Let's run our first code in Jupyter Notebook.

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So if I am going to write one plus one.

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So here you can see I'm getting an error running cell with v and v.

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Python 3.20120 requires the ipykernel package.

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Okay, so this is one of the requirement that we really need to do.

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Uh, we need to install Ipykernel.

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Okay.

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So here I'm what I'm going to write is that pip install.

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If I want to install any packages I have to just go ahead and write pip install Ipykernel.

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Okay.

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So once I probably do this you'll be able to see that if I press enter you'll be seeing that hey, my

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Ipykernel is basically getting installed now.

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What is this Ipykernel package?

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Ipykernel package is nothing, but it provides a kernel to this specific Jupyter notebook, which will

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be responsible in executing the Python code, right?

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It is pretty much necessary and compulsory in Anaconda.

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The default Jupyter notebook has Ipykernel already integrated to it.

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Okay, so this is the first thing that you really need to do.

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Whenever you want to run the Jupyter notebook, you just go ahead and right pip install Ipykernel.

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One more thing that you can actually do is that here what I will do, I will go ahead and create one

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requirement dot txt because this requirement dot txt you know later on whatever packages I want.

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Let's say the first package I want is Ipykernel.

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I'll keep a note of this over here and any number of packages I will be requiring, let's say in the

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future classes you'll be seeing pandas, numpy, different different packages.

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So we will try to install it from here itself.

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We'll write over here and we'll run this requirement dot txt which will be responsible in installing

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all the packages.

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Now you can see that uh, the Ipykernel has got successfully executed.

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Now let me just go ahead and run this same code.

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So here you'll be able to see if I run the same code.

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Now it is just going to execute.

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It is saying that connecting to Colonel.

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And here I am having my output.

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Right.

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So now I can probably go ahead and write any type of code that I want.

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Let's say I want to go ahead and write.

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Print.

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Hello hello world.

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Okay.

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Something like this.

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So here we'll be able to see that it is executing right for.py file.

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I don't want any type of colonel because in the terminal in the terminal automatically that particular

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terminal uh, has this environment set up.

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Right.

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So in order to execute it I have to go ahead and write Python app dot p y, right.

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Or whatever is the file name.

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In this case, if I want to execute any cell, I have to just press that particular cell and press shift

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enter.

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Okay.

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So in this video we have discussed about how you can go ahead and create your environment.

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because going forward, any session that is probably going to come up in this course, I'm going to

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probably create a folder wise like this.

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For first class, I will probably create Python basics, create my Jupyter notebook file or.py file,

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execute all the code in front of you, write all the code in front of you and continue right.

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So for right now, I will just go ahead and delete this folder because I don't require it.

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Because at the end of the day, I will do one thing.

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Okay, just a second.

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I will just close this, okay?

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Yeah.

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Now let me just go ahead and delete it, because in the next session I will go ahead and create everything

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from scratch requirement dot txt I will keep it so that I keep on updating my packages.

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So yes, this was it for my side.

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I hope you like this video.

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And in the next video we will start our Python basics.

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So yes, this was it.

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Thank you.

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Take care.

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Bye bye.