feat: language identification project page

Author: bitmap4

src/content/docs/index.mdx

@@ -8,7 +8,7 @@ hero:
     file: ../../assets/houston.webp
   actions:
     - text: Stuff I've Made
-      link: /projects/placeholder
+      link: /projects/lid
       icon: right-arrow
     - text: Resume
       link: https://drive.google.com/file/d/1L8lr5-B45VnHHbTIvZRya9fNBJOjI8h3/

src/content/docs/projects/lid.md

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+---
+title: Language Identification Analysis
+description: A comparative study of various language classifiers based on different combinations of linguistic features vs a baseline n-grams based model
+---
+
+## About the Project
+
+A machine learning system for identifying Hindi and Marathi text written in Devanagari script using multiple feature extraction techniques and classification models for a comparative study. The classifiers used were both Naive Bayes. This is my course project for the course CL2 (Computational Linguistics 2).
+
+[`GitHub`](https://github.com/bitmap4/language-identification-analysis)
+[`Report`](https://drive.google.com/file/d/1AOhGJupvoLIHYv3SttUXIJ8m7ax3K5HE)
+
+
+## Features
+
+- Supports Hindi and Marathi language identification
+- Multiple feature extraction methods:
+  - Character frequency analysis 
+  - Word length statistics
+  - Character class distribution (vowels, consonants, matras)
+  - N-gram analysis
+  - Morphological analysis
+  - POS tagging features (optional)
+  - TF-IDF features
+
+## Setup
+
+Run `setup.sh` to install required packages and download necessary data files.
+
+## Usage
+
+Run all cells in `model_comparison.ipynb`
+> Create a directory named `<data_size>` in case it is not created automatically on running the notebook.
+
+## Results
+
+Results of the model comparison are available in `results/<data_size>` where `<data_size>` is the configured size of the training + testing data used for the models.