Doctoral Researcher @ NTHU (Machine Learning / AI), web developer, founder, designer, blogger, and open-source advocate.
Deep Learning for NLP: PyTorch vs Tensorflow
- Location: R0
- Slot: Day 2, 11:15‑12:00
- Category: Data Analysis
- Language: English talk
- Python Level: Intermediate
In this talk, I will 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.