Homework's Need To Be Submitted In GitHub I Will Share GitHub Details With You Later
uazhlt-ms-program / pa-transition-parser-harsha2309 Private pa-transition-parser-harsha2309 created by GitHub Classroom 0 stars 0 forks Code Issues Pull requests 1 Actions Projects Wiki Security View code Programming Assignment: Transition-based dependency parser Learning objectives 1. practice working with dependency tree data 2. become familiar with training transition-based parsers Your assignment You will implement two functions, read_conllu and parse , and two methods for each of two classes, Oracle and Classifier . A template for each of these has been provided in the assignment.ipynb file. You should read the documentation strings (docstrings) in each of methods in that file, and implement the methods as described. The following objects and functions may come in handy: collections.deque sklearn.feature_extraction.DictVectorizer Star Watch main github-classroom Setting up GitHub Classroom Feedback … 1 minute ago 3 https://github.com/uazhlt-ms-program https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309 https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/stargazers https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/network/members https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309 https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/issues https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/pulls https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/actions https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/projects https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/wiki https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/security https://docs.python.org/3/library/collections.html#collections.deque https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/commits?author=github-classroom%5Bbot%5D https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/commit/8e8f4ceb45a9a39398529097a0ca7dd662fd442d https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/commit/8e8f4ceb45a9a39398529097a0ca7dd662fd442d https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/commits/main https://github.com/apps/github-classroom sklearn.preprocessing.LabelEncoder sklearn.linear_model.LogisticRegression Prerequisites You should be using the Linux development environment you set up at the beginning of the course. From your Ubuntu environment, ensure that you have ... docker A modern web browser Ex. Firefox or Chrome/Chromium Getting started This assignment is intended to be run using docker . You are provided a number of unit tests to help develop and refine your solution. The tests can be found in the included Jupyter notebook. Your code will be tested using the published docker image. You should not use any additional third-party libraries to develop your solution. Please note that additional dependencies you install will be ignored during testing. Running the assignment # NOTE: this incantation assumes you're running the command # from the project root (i.e., the directory containing this README). # Changes to files under notebooks will be written from client to host. docker run -it -p 7777:9999 -v "$PWD:/app/" uazhlt/pa-transition-parser:latest From within your Linux VM, open your browser to localhost:7777 and navigate to assignment.ipynb . Submitting your assignment Commit your solution for assignment.ipynb using git and push to the main branch of your remote repository. For example, you could use the following workflow: README.md https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html https://parsertongue.org/tutorials/ubuntu-install-docker/ https://docs.docker.com/install/ https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/blob/main/assignment.ipynb https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/edit/main/README.md To help track your progress, feel free to commit and push as many times as you like. Only the most recent commit before the deadline will be graded. Misc Type hints To help with debugging, this assignment makes use of Python type hints. Unfamiliar with git ? You may find these links useful: https://parsertongue.org/tutorials/git-basics https://parsertongue.org/tutorials/github-intro Unfamiliar with docker ? You may find these links useful: https://parsertongue.org/tutorials/docker-intro https://parsertongue.org/tutorials/containers-intro Removing old docker containers, images, etc. If you want to save some space on your machine by removing images and containers you're no longer using, see the instructions here. As always, use caution when deleting things. # Step 1: Make your changes and stage your progress (i.e., tell git you want to "sav git add assignment.ipynb # Step 2: Commit your changes. # Change the message to reflect the nature of your changes git commit -m "Complete solution" # Step 3: Submit your changes by pushing them to the main branch of your remote repo git push origin main https://docs.python.org/3.8/library/typing.html https://parsertongue.org/tutorials/git-basics https://parsertongue.org/tutorials/github-intro https://parsertongue.org/tutorials/docker-intro https://parsertongue.org/tutorials/containers-intro https://docs.docker.com/config/pruning/ Releases No releases published Create a new release Packages No packages published Publish your first package Languages Jupyter Notebook 100.0% https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/releases https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/releases/new https://github.com/orgs/uazhlt-ms-program/packages?repo_name=pa-transition-parser-harsha2309 https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/packages https://github.com/uazhlt-ms-program/pa-transition-parser-harsha2309/search?l=jupyter-notebook uazhlt-ms-program / pa-getting-started-harsha2309 Private pa-getting-started-harsha2309 created by GitHub Classroom 0 stars 0 forks Code Issues Pull requests 1 Actions Projects Wiki Security View code Programming assignment: Getting started NOTE: This assignment should be launched and completed from the Linux VM you configured as part of the first Unit. Learning objectives 1. Become comfortable with the structure of assignments git, GitHub Classroom, docker , and Jupyter notebooks 2. Demonstrate the ability to complete simple Python functions Your assignment Follow the instructions in assignment.ipynb . For the coding problems, you will be provided with test cases. Prerequisites Star Watch main github-classroom Setting up GitHub Classroom Feedback … on Mar 21 3 README.md https://github.com/uazhlt-ms-program https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309 https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/stargazers https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/network/members https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309 https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/issues https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/pulls https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/actions https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/projects https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/wiki https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/security https://git-scm.com/downloads https://docs.docker.com/install/ https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_is_jupyter.html https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/commits?author=github-classroom%5Bbot%5D https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/commit/60c8f543613c90bbda2d2acf47aa9c517b4ea5f9 https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/commit/60c8f543613c90bbda2d2acf47aa9c517b4ea5f9 https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/commits/main https://github.com/apps/github-classroom https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/edit/main/README.md You should be using the Linux development environment you set up at the beginning of the course. From your Ubuntu environment, ensure that you have ... docker A modern web browser Ex. Firefox or Chrome/Chromium Getting started This assignment is intended to be run using docker . You are provided a number of unit tests to help develop and refine your solution. The tests can be found in the included Jupyter notebook. Your code will be tested using the published docker image. You should not use any additional third-party libraries to develop your solution. Please note that additional dependencies you install will be ignored during testing. Running the assignment # NOTE: this incantation assumes you're running the command # from the project root (i.e., the directory containing this README). # Changes to files under notebooks will be written from client to host. docker run -it -p 7777:9999 -v "$PWD:/app/" uazhlt/pa-getting-started:latest From within your Linux VM, open your browser to localhost:7777 and navigate to assignment.ipynb . Submitting your assignment Commit your solution for assignment.ipynb using git and push to the main branch of your remote repository. For example, you could use the following workflow: # Step 1: Make your changes and stage your progress (i.e., tell git you want to "sav git add assignment.ipynb # Step 2: Commit your changes. # Change the message to reflect the nature of your changes git commit -m "Complete solution" https://parsertongue.org/tutorials/ubuntu-install-docker/ https://docs.docker.com/install/ https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/blob/main/assignment.ipynb To help track your progress, feel free to commit and push as many times as you like. Only the most recent commit before the deadline will be graded. Misc Type hints To help with debugging, this assignment makes use of Python type hints. Unfamiliar with git ? You may find these links useful: https://parsertongue.org/tutorials/git-basics https://parsertongue.org/tutorials/github-intro Unfamiliar with docker ? You may find these links useful: https://parsertongue.org/tutorials/docker-intro https://parsertongue.org/tutorials/containers-intro Removing old docker containers, images, etc. If you want to save some space on your machine by removing images and containers you're no longer using, see the instructions here. As always, use caution when deleting things. Releases No releases published Create a new release # Step 3: Submit your changes by pushing them to the main branch of your remote repo git push origin main https://docs.python.org/3.8/library/typing.html https://parsertongue.org/tutorials/git-basics https://parsertongue.org/tutorials/github-intro https://parsertongue.org/tutorials/docker-intro https://parsertongue.org/tutorials/containers-intro https://docs.docker.com/config/pruning/ https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/releases https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/releases/new Packages No packages published Publish your first package Languages Jupyter Notebook 100.0% https://github.com/orgs/uazhlt-ms-program/packages?repo_name=pa-getting-started-harsha2309 https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/packages https://github.com/uazhlt-ms-program/pa-getting-started-harsha2309/search?l=jupyter-notebook uazhlt-ms-program / pa-memm-classifier-harsha2309 Private pa-memm-classifier-harsha2309 created by GitHub Classroom 0 stars 0 forks Code Issues Pull requests 1 Actions Projects Wiki Security View code Programming Assignment: MEMM classifier Learning objectives 1. Practice working with sequential part-of-speech tagging data 2. Become familiar with training maximum entropy Markov models (MEMMs) Your assignment You will implement one function, read_ptbtagged , and six methods of a class, Classifier . A template for each of these has been provided in the assignment.ipynb file. You should read the documentation strings (docstrings) in each of methods in that file, and implement the methods as described. The following objects and functions may come in handy: sklearn.feature_extraction.DictVectorizer sklearn.preprocessing.LabelEncoder sklearn.linear_model.LogisticRegression Star Watch main github-classroom Setting up GitHub Classroom Feedback … 11 minutes ago 3 README.md https://github.com/uazhlt-ms-program https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309 https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/stargazers https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/network/members https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309 https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/issues https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/pulls https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/actions https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/projects https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/wiki https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/security https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/commits?author=github-classroom%5Bbot%5D https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/commit/d7894b7e5dffab25cbfc741b56dc20a0ae2e9793 https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/commit/d7894b7e5dffab25cbfc741b56dc20a0ae2e9793 https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/commits/main https://github.com/apps/github-classroom https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/edit/main/README.md scipy.sparse.vstack numpy.argmax Prerequisites You should be using the Linux development environment you set up at the beginning of the course. From your Ubuntu environment, ensure that you have ... docker A modern web browser Ex. Firefox or Chrome/Chromium Getting started This assignment is intended to be run using docker . You are provided a number of unit tests to help develop and refine your solution. The tests can be found in the included Jupyter notebook. Your code will be tested using the published docker image. You should not use any additional third-party libraries to develop your solution. Please note that additional dependencies you install will be ignored during testing. Running the assignment # NOTE: this incantation assumes you're running the command # from the project root (i.e., the directory containing this README). # Changes to files under notebooks will be written from client to host. docker run -it -p 7777:9999 -v "$PWD:/app/" uazhlt/pa-memm-classifier:latest From within your Linux VM, open your browser to localhost:7777 and navigate to assignment.ipynb . Submitting your assignment Commit your solution for assignment.ipynb using git and push to the main branch of your remote repository. For example, you could use the following workflow: https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.vstack.html https://docs.scipy.org/doc/numpy/reference/generated/numpy.argmax.html https://parsertongue.org/tutorials/ubuntu-install-docker/ https://docs.docker.com/install/ https://github.com/uazhlt-ms-program/pa-memm-classifier-harsha2309/blob/main/assignment.ipynb To help track your progress, feel free to commit and push as many times as you like. Only the most recent commit before the deadline will be graded. Misc Type hints To help with debugging, this assignment makes use of Python type hints. Unfamiliar with git ? You may find these links useful: https://parsertongue.org/tutorials/git-basics https://parsertongue.org/tutorials/github-intro Unfamiliar with docker ? You may find these links useful: https://parsertongue.org/tutorials/docker-intro https://parsertongue.org/tutorials/containers-intro Removing old docker containers, images, etc. If you want to save some space on your machine by removing images and containers you're no longer using, see the instructions here. As always, use caution when deleting things. # Step 1: Make your changes and stage your progress (i.e., tell git you want to "sav git add assignment.ipynb # Step 2: Commit your changes. # Change the message to reflect the nature of your changes git commit -m "Complete solution" # Step 3: Submit your changes by pushing them to the main branch of your remote repo git push origin main https://docs.python.org/3.8/library/typing.html https://parsertongue.org/tutorials/git-basics https://parsertongue.org/tutorials/github-intro https://parsertongue.org/tutorials/docker-intro https://parsertongue.org/tutorials/containers-intro https://docs.docker.com/config/pruning/ Releases No releases published Create a new release Packages No packages published Publish your first