I am currently working on a graduate study at a top 30 university in the United States and have become very interested in deep learning neural networks. During our Artificial Intelligence (AI) course, we have learned a framework called Keras to build the Neural Network. The tutor of this course does not talk more about the algorithms and rationale behind those easy-composed codes, since nearly everybody nowadays enjoys using those preset frameworks like Tensorflow, Keras, Pytorch to develop a various neural network. I don’t think that is the best way for students to learn deep learning. …

Today I will introduce a model that merges an Attention-based RNN and a fully-connected neural network to predict a customer’s conversion rate and assign credits to different digital channels. The complete code can be found here. My work is mostly inspired by a paper written by Ning Li, etc.

co-authors: Nanxi Wang, Shea Thomas; co-editors: Haolin Hong, Nancy Fei

Find the code here; For beginners, a simple way is to initialize class ‘process’ and ‘model’, using the functions in the code to transform (model.dtm) and train your own text data (model.nb_logreg) for sentiment or other classification analysis.

Natural Language Processing (NLP) is a big topic in the area of content management for the online platform where people are free to post their opinions, questions and so forth. Many websites are facing how to handle the toxic and divisive content so as to provide their audience with a more comfortable…