Purpose of this project was to utilize various NLP techniques including LDA for topic modeling and perform sentiment analysis on Technology articles collected from The New York Times. Dataset corpus was preprocessed applying various text cleaning techniques using NLTK library. LDA was applied to find the most common topics and PyLDAvis was used to visualize them. Lastly, sentiment analysis was carried out using TextBlob library to get an insight into sentiments hidden in text.