{"id":27433900,"url":"https://github.com/cliche-niche/cs253","last_synced_at":"2025-10-14T14:16:01.991Z","repository":{"id":67125640,"uuid":"473696435","full_name":"cliche-niche/CS253","owner":"cliche-niche","description":"Contains the assignment submissions made in the course CS253 \"Software Development and Operations\" in the 2021-22 II Sem. 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All three submissions were satisfactory (with respect to the rubric atleast). The assignments have been explained briefly below:\n\n+ [\u003cu\u003eC++:\u003c/u\u003e](./C%2B%2B/) A library management system had to be implemented with some classes and functions given, but we were free to expand on them.\u003cbr\u003e\nMarks Distribution:\n\u003cdiv align=\"center\"\u003e\n\n| Functionality |  Marks   |\n|:---------:|:--------:|\n|Class structure, Good coding practices | 10.0 |\n|Login-Logout Functionality | 2.0 |\n|Student's functionalities | 6.0 |\n|Professor's functionalities | 6.0 |\n|Book Class functionalities | 6.0 |\n|Librarian's functionalities | 10.0 |\n\u003c/div\u003e\n\n+ [\u003cu\u003eBash:\u003c/u\u003e](./Bash/) A script that parses a given `.CSV` and prints some fields to a given output file.\u003cbr\u003e\nMarks Distribution:\n\u003cdiv align=\"center\"\u003e\n\n| Question |  Marks   |\n|:---------:|:--------:|\n|Question 1|3.0|\n|Question 2|3.0|\n|Question 3|5.0|\n|Question 4|5.0|\n|Question 5|8.0|\n|Question 6|6.0|\n\u003c/div\u003e\n\n+ [\u003cu\u003ePython:\u003c/u\u003e](./Python/) A `.ipynb` in which templates of some functions were given that were going to be used in an ML-based classifier (that classifies emails as spam or not spam). The algorithms used were SVM and KNN.\nBefore running, please ensure that the dataset is stored in an appropriately named file in the same directory as the [.ipynb](./Python/Assignment.ipynb).\u003cbr\u003e\nMarks Distribution:\n  + Data pre-processing (11): 1.0 for `read_email()`, 2.0 for the rest of the functions\n  + Visualization (5): 2.0 for all emails, 1.0 for spam emails, 1.0 for non-spam emails, 1.0 for correct annotations in graphs.\n  + Classification (9): 3.0 for splitting, SVM, KNN classifier each.\n  + Model Evaluation (6): 3.0 for accuracy and AUC score each.\n\n\n### Acknowledgements\n\nNot all the files included in this repository are my own. The assignment files in [Bash](./Bash/Assignment.pdf) and [C++](./C%2B%2B/Assignment.pdf) were provided in the course, and the [Jupyter Notebook](./Python/Assignment.ipynb) was also provided with some instructions, links and templates written.\u003cbr\u003e\nFurther, the [file](./Bash/college.csv) used as the input for the bash script was also provided in the course.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcliche-niche%2Fcs253","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcliche-niche%2Fcs253","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcliche-niche%2Fcs253/lists"}