  Theedhum Nandrum is a sentiment polarity detection system using two
approaches--a Stochastic Gradient Descent (SGD) based classifier and a Long
Short-term Memory (LSTM) based Classifier. Our approach utilises language
features like use of emoji, choice of scripts and code mixing which appeared
quite marked in the datasets specified for the Dravidian Codemix - FIRE 2020
task. The hyperparameters for the SGD were tuned using GridSearchCV. Our system
was ranked 4th in Tamil-English with a weighted average F1 score of 0.62 and
9th in Malayalam-English with a score of 0.65. We achieved a weighted average
F1 score of 0.77 for Tamil-English using a Logistic Regression based model
after the task deadline. This performance betters the top ranked classifier on
this dataset by a wide margin. Our use of language-specific Soundex to
harmonise the spelling variants in code-mixed data appears to be a novel
application of Soundex. Our complete code is published in github at
https://github.com/oligoglot/theedhum-nandrum.
