Language Detection Model Data set : https://www.kaggle.com/datasets/basilb2s/language-detection Steps Followed 1. Load the data set 2. Encode the labels into categoical form 3. Pre-process the Text content 4. Tokenizing 5. Create a Dictionary for Vocabulary 6. Count the Word Frequencies (Unigrams were considered) 7. Split the dataset into train and test sets 8. Perform Supervised Classification Could achieve 97.3% accuracy using Naive Bayes Classifier