Using Gensim's Doc2Vec models (DM and DBOW) classify sentiments using Logistic, SVM, SGD and Deep Belief Network

PPT will walk through the entire process of the case study and the approach

Part 1) Scraping amazon product review and identifying Positive/Negative classes using Lexicon approach (this is in R)

Part 2a) Working on the scrapped reviews and creating Doc2Vev vectors using gensim package and both models (DM and DBOW) (This is in Python 3)

Part 2b) This is continuation of Part 2 Classification algorithm using Deep Belief Network from nolearn package (Only for Python 2.7.3)

If you have any questions, shoot me an email at [email protected]