Applied AI: Building NLP Apps with Hugging Face Transformers

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Kumaran Ponnambalam

57:27

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01 - Introduction

01 - Building NLP apps with Transformers.mp4

00:50

02 - Course coverage and prerequisites.mp4

02:36

03 - Setting up the exercise files.mp4

03:01

02 - 1. Question-Answering (Qu-An)

04 - Question-answering in NLP.mp4

01:50

05 - Types of question-answering.mp4

01:43

06 - Building a Qu-An pipeline.mp4

01:52

07 - The SQuAD metric.mp4

01:44

08 - Evaluating Qu-An performance.mp4

02:02

03 - 2. Text Summarization

09 - Text summarization in NLP.mp4

02:24

10 - The BART model architecture.mp4

00:53

11 - Summarization with pipelines.mp4

01:36

12 - The ROUGE score.mp4

01:10

13 - Evaluating with ROUGE.mp4

01:33

04 - 3. Natural Language Generation

14 - Natural language generation in NLP.mp4

01:52

15 - Content creation with Transformers.mp4

01:41

16 - Conversation generation.mp4

01:21

17 - Chatbot conversation example.mp4

01:57

18 - Machine translation in NLP.mp4

01:31

19 - Translating with Hugging Face Transformers.mp4

02:13

05 - 4. Customizing Models with Transfer Learning

20 - Training a custom model.mp4

01:44

21 - Loading a Hugging Face dataset.mp4

02:23

22 - Encoding and preprocessing the dataset.mp4

02:41

23 - Customizing the model architecture.mp4

02:19

24 - Training the sentiment model.mp4

01:46

25 - Predicting with the custom model.mp4

02:14

06 - 5. Deploying and Using Hugging Face Models

26 - Inference challenges with Transformers.mp4

02:19

27 - Customizing pretrained models.mp4

01:50

28 - Model compression overview.mp4

02:27

29 - Serving multiple models.mp4

03:19

07 - Conclusion

30 - Continuing with Hugging Face.mp4

00:36

Description

Looking to expand your skill set in deep learning? Find out how to use Hugging Face transformers to build natural language processing (NLP) applications. In this course, instructor Kumaran Ponnambalam shows you how to build models quickly and easily using pretrained transformers from the Hugging Face library.

Explore models designed for common NLP use cases such as question-answering, text summarization, text generation, translation, and more. Kumaran gives you tips for customizing models with transfer learning to meet the needs of specific use cases—improving your performance and lowering your costs along the way. Develop your know-how to identify and overcome common modeling challenges to ensure successful, error-free deployments. By the end of this course, you’ll be ready to adhere to the best practices and industry standards when you start applying your new skills on the job.

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Artificial Intelligence

Natural Language Processing

Kumaran Ponnambalam

Instructor's Courses

A seasoned veteran in everything data, with a reputation for delivering high performance database and SaaS applications and currently specializing in leading Big Data Science and Engineering efforts

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