https://github.com/happybravo/iisc_selectionproblems

My solutions for IISc selection-problems
https://github.com/happybravo/iisc_selectionproblems

bert-embeddings classification data-science iisc iisc-bangalore llm machine-learning nlp problem-solving python regression vectorization

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My solutions for IISc selection-problems

• Host: GitHub
• URL: https://github.com/happybravo/iisc_selectionproblems
• Owner: HappyBravo
• Created: 2024-04-27T22:33:39.000Z (8 months ago)
• Default Branch: master
• Last Pushed: 2024-04-28T18:02:23.000Z (8 months ago)
• Last Synced: 2024-11-08T15:36:00.701Z (about 2 months ago)
• Topics: bert-embeddings, classification, data-science, iisc, iisc-bangalore, llm, machine-learning, nlp, problem-solving, python, regression, vectorization
• Language: Jupyter Notebook
• Homepage:
• Size: 20.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# My Solutions for Problem 1 and 2 

## Questions can be found [here](https://github.com/StarsCDS/selection-problems).

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## [Solution for Problem 1](./Problem_1/)

- incorporating new features within the model to achieve more accurate predictions.

- utilized regression techniques to forecast the timing of the next movie.

- used classification techniques to classify movie genres.

## [Solution for Problem 2](./Problem_2/)

- the data files are stored in the required format for further processing.

- [One-hot encoding](https://www.geeksforgeeks.org/ml-one-hot-encoding/) is applied to categorical features within the dataset. 

- [BERT](https://huggingface.co/google-bert/bert-base-uncased) was employed to generate vector representations from textual data.