Designed a Machine Learning model which takes in different newsgroup text corpus and performs binary classification to predict if a given document has Atheistic or Christian sentiment to validate sentiment analysis with spark data pipeline and calculated F1-score, accuracy and class probabilities. Used LIME and PySpark and Spark MLlib. Performed feature selection to improve the classifier’s performance.