English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 0h 41m | 118 MB
Learn about natural language processing with PyTorch, the popular deep learning tool used by tech giants like OpenAI and Microsoft. In this course, Zhongyu Pan guides you through the basics of using PyTorch in natural language processing (NLP). She explains how to transform text into datasets that you can feed into deep learning models. Zhongyu walks you through a text classification project with two frequently used deep learning models for NLP: RNN and CNN. She also shows you how to tune hyperparameters and construct model layers to get more robust and accurate results, as well as the differences between the two models for NLP tasks.
Table of Contents
Introduction
1 Welcome
2 What you should know
NLP with Deep Learning Introduction
3 Popular topics in NLP
4 Introducing deep learning
PyTorch Basics
5 Why PyTorch
6 PyTorch tensor
Guided Project CNN Text Classification with PyTorch
7 Preprocessing text dataset
8 Building a simple CNN model
9 Train and evaluate functions
10 Challenge Training process
11 Solution Training process
Conclusion
12 Keep learning and connect
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