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airline-dataset

disaster-management

eliza_chatbot

forecast-analysis

Performed data cleansing and Forecast analysis using ARIMA techniques on the superstore sales dataset using python. Predicted the sales for the future years and compared different values in the dataset and predictions are showed.

malware-analysis-on-hardware

ml_projects

n-grams

network-sentiment-analysis-on-social-media

Sentiments are predicted on the #Autism Tweets and Instagram posts and classified them into different categories. Network Analysis is performed to know the relationship between the Users and the posts. Concluded Instagram platform is more positive compared to Twitter.

pos-tagger

sentiment-analysis-on-us-airline

Performed Sentiment Analysis on the US airline dataset using python Numpy and Pandas, data cleansing and used Bag of Words and TF-IDF for data preprocessing. Built the model by running different Machine Learning and NLP techniques such as KNN, Support Vector Machine, Decision tree, Random Forest, Logistic Regression, Naïve Bayes and cross-validation is performed and identified best model. Visualization is done by python.

word-sense-disambiguation

Word Sense Disambiguation (WSD): This program helps us identify which sense of a word is used in a sentence when a word has multiple meanings. WSD is an open problem of natural language processing and ontology. The main challenge in this program is to create a classifier which identifies the sense of the words (which can be used for multiple meanings) based on the input file.