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airline-delay-performance-analysis-using-sas

anime-recommendation-system

Project in Python - using Pyspark - Covers techniques including Recommendation system using Matrix factorization, using Alternate Least Squares, K-nearest neighbor and TFIDF features from movie reviews

german-credit---binary-classification

hbr---manipal-hospitals---predicting-net-promotor-score

hbr---vmware-multiclass-classification---propensity-to-respond-model

Project uses various techniques on exploratory data analysis, feature engineering and class-balancing. Random Forest, Regularized Logistic regression and Gradient Boosting models were tuned using Cross-validation in order to identify potential customers based on historical data from customers' purchase behavior, campaign-specific transaction data and customer activity data

k-means-clustering---prospect-customer-segmentation

mapreduce-implementation-for-word-frequency-count-using-pyspark

Project in Python - using Pyspark - Building MapReduce for calculating word frequency on twitter dataset, using Spark dataframes

nd027-c3-data-lakes-with-spark

sentiment-analysis-using-bag-of-words-tfidf-features-and-recurrent-neural-net

Conducted sentiment classification on Sentiment140 twitter dataset,in Python, using NLTK, Bag of Words, TFIDF features and Recurrent neural network.

streaming-tweets-with-tweepy-visualing-tweets-using-plotly-real-time-topic-tracking-with-dash

wine-quality-prediction---binalry-classification