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Elvis Saravia

Evolving the learning experience

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In this talk, I discuss some of the best practices and latest trends in natural language processing (NLP) research. The main goal is to provide a comprehensive comparison between machine learning frameworks (PyTorch and Tensorflow) when used for NLP-related tasks, such as sentiment analysis and emotion recognition from textual data. I will cover how to program and train widely-used algorithms, such as neural word embeddings and long short-term memory (LSTM) networks, for sentence classification. I will discuss some challenges and opportunities in deep learning for NLP research together with the advantages and disadvantages of using PyTorch and Tensorflow.

Slides