Building 1D Convolutional Neural Network Model in Keras for Sentimental Analysis

Full Title:
Building 1D Convolutional Neural Network Model with Word Embedding in Keras for Sentimental Analysis on IMDB Reviews

Abstract:
Natural language processing (NLP) with deep learning is an important combination of techniques in machine learning. Word embedding is one of the most important concepts in NLP for representing words and documents using vectors. Keras is a highly popular deep learning library. Using word vector representations and embedding layers, you can train a CNN (Convolutional Neural Network) in Keras for sentimental analysis on a large dataset of IMDB movie reviews.

Short Bio:
Joan Zhang is a database professional with data science skills. She has a strong performance track record across high-tech, banking, healthcare and pharmacy. She worked as DB2 lead database architect for WBA and database management at HSBC and IBM. Joan holds a bachelor’s degree in Business Computing from the University of Winnipeg and a master’s degree in Analytics from The University of Chicago.

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