[SOLVED] Cs6601 assignment 0 – python/jupyter/gradescope

Name: [SOLVED] Cs6601 assignment 0 – python/jupyter/gradescope
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This assignment is designed to help you prepare your local python environment, introduce you to jupyter notebooks and provide a refresher on python language. After following this README you will have a python environment ready and will be able to proceed with learning about jupyter notebooks in the `notebook.ipynb` (where you will make your first graded submission!). Let’s get started!### Table of Contents
– [Get repository](#repo)
– [Conda](#conda)
– [Environment](#env)
– [Packages](#pkg)
– [Jupyter](#jupyter)
– [Summary](#summary)<a name=”repo”/></a>
## Get repositoryFirst things first, let’s pull this repository to your local machine:“`
git clone https://github.gatech.edu/omscs6601/assignment_0.git
“`Then come back to this README to continue with further setup.<a name=”fork-instructions”/></a>
## Instructions to create a private forked repository for assignmentsThe assignments you would be working on throughout this semester will potentially require multiple revisions. A good way to track these revisions is by using your own private repo to backup your assignments at various stages of completion. Please remember that your assignment repository should be private and only accessible to yourself so that you do not accidentally violate the OSI policy. You can use the following steps to create a private repository for assignment 0. Please replace the A0 url with the future assignments’ URL to repeat this for the future assignments. * Login to github.gatech.edu and create a private repo named : YOUR_REPO. Double check that the repo is private, otherwise you may violate the OSI policy* Get the class repo “git clone –bare https://github.gatech.edu/omscs6601/assignment_0.git“* Mirror this to your private repo 
“`
cd assignment_0.git
git push –mirror https://github.gatech.edu/your_gatech_id/YOUR_REPO
“`* You can now delete the “assignment_0.git“ directory cloned two steps ago if you wish.* Now clone your private repo on your local system “git clone https://github.gatech.edu/your_gatech_id/YOUR_REPO“* Next 
“`
cd YOUR_REPO
git remote add upstream https://github.gatech.edu/omscs6601/assignment_0.git
“`
You check if the remote branch has been added using “git remote -v“* Now you can use it like this 
“`
git pull upstream master # the original repo
git push origin master # your repo
“`
If you do not specify the remote, it will default to the origin (your repo)* If you are scared of pushing to upstream you can disable pushing to upstream using “git remote set-url –push upstream PUSH_DISABLED“<a name=”conda”/></a>
## Conda![Conda Logo](https://conda.io/en/latest/_images/conda_logo.svg)Conda is an open source package and environment management system. Conda quickly installs, runs and updates packages/libraries and easily creates, saves, loads, and switches between environments on your local computer.Please download [Miniconda](https://docs.conda.io/en/latest/miniconda.html) and install it on your local machine. Although we require Python 3.7 for this course, you should install the version of Miniconda for any Python 3 version (e.g. Python 3.x). You can override this default by specifying the python version as 3.7 when creating the environment you will be working in for this course. You can access conda via the console to make sure it’s properly installed. For instance, you can run `conda -V` to display the version.On Windows, to access `conda` via the console please use “Anaconda Prompt” or “Anaconda Powershell Prompt” instead of “Command Prompt”.<a name=”env”/></a>
## EnvironmentEnvironments are used to keep different python versions and packages isolated from each other, generally each project/application will have an independent python environment. For example, we will be using Python 3.7 and packages like numpy, networkx etc, and we want them to be isolated from any other python projects you might have.To create a new environment simply run:“`
conda create –name ai_env python=3.7 -y
“`Once it’s created you can activate it by running:“`
conda activate ai_env
“`The environment is not attached to any specific folder, and you can freely navigate to different directories while it’s activated. If you want to change the environment you can deactivate it using `conda deactivate` and then activate another env. To see the list of all environments you have on your machine you can run `conda env list`.<a name=”pkg”/></a>
## Packages![Python Logo](https://www.python.org/static/community_logos/python-logo-master-v3-TM.png)We will be using multiple python packages throughout this class. Here are some of them:* **jupyter** – interactive notebook (you will learn more about them soon)
* **numpy** – a package for scientific computing (multi-dimensional array manipulation)
* **matplotlib** – a plotting library
* **networkx** – a package for manipulating networks/graphs
* **pandas** – a package for data analysis
* **pgmpy** – library for probabilistic graphical modelsYou can see the complete list of packages and required versions in [./requirements.txt](./requirements.txt).We can install all these packages using command “pip install -r requirements.txt“. Please navigate to the `assignment_0/` directory, activate your environment (`conda activate ai_env`), then run:“`
pip install -r requirements.txt
“`Once installed, you can run `pip freeze` to see the list of all of the packages installed in your `ai_env` environment.> **Note:** If you are on Windows, students in the past have commonly reported an error during package installation that resembles the error in this [Github post](https://github.com/pytorch/pytorch/issues/34798). To fix this issue, head over to the [PyTorch site](https://pytorch.org) and follow the instructions to install torch manually in `ai_env`. If this does not work, you may also instead try running `conda install -c ankurankan pgmpy=0.1.10`. After trying one of the previous suggestions and getting a successful install, try `pip install -r requirements.txt` again.<a name=”jupyter”/></a>
## Jupyter![Jupyter Logo](https://jupyter.org/assets/nav_logo.svg)Now that you have set up the environment it’s time to learn more about the jupyter notebooks.We have already installed jupyter. To open it up you can run:“`
jupyter notebook
“`It will start a python kernel which you can access via [https://localhost:8888](https://localhost:8888/) in your browser. For the rest of the assignment proceed to `notebook.ipynb`.<a name=”summary”/></a>
## SummaryYou have now installed conda package and environment manager, created a python environment and installed all the necessary packages.Please always remember to run:
“`
conda activate ai_env
“`
to activate your environment before you start working on your assignments.