
Udemy – Natural Language Processing: NLP With Transformers in Python 2022-8
Published on: 2023-06-30 21:50:43
Categories: 28
Description
Natural Language Processing: NLP With Transformers in Python is a course on learning natural language processing with transformers using the tools of PyTorch, TensorFlow, HuggingFace and more. Transformer models are a standard in modern natural language processing. In this course, you will build high-performance natural language processing programs using transformer models such as Google Artificial Intelligence (BERT) or Facebook Artificial Intelligence (DPR).
What you will learn in Natural Language Processing: NLP With Transformers in Python:
- Industrial standard for natural language processing using Transformer models
- Build complete question-answer transformer models
- Perform emotion analysis with transformer models using PyTorch and TensorFlow
- Advanced search technology such as Elasticsearch and Facebook Match Search Artificial Intelligence (FAISS)
- Measuring the effectiveness of language models using advanced metrics such as ROUGE
- Vector manufacturing technology such as BM25 or dense passage retrievers (DPR)
- An overview of recent advances in natural language processing
- Understand the attention and other key components of transformers
- Text data preprocessing for NLP
Course specifications
Publisher: Udemy
Instructors: James Briggs
Language: English
Level: Advanced to Advanced
Number of Courses: 104
Duration: 11 hours and 30 minutes
Course topics:

Course prerequisites:
Experience in data science a plus
Pictures

Sample film
Installation guide
After Extract, watch with your favorite Player.
Subtitle: English
Quality: 1080p
Previous title:
Natural language processing with transformers in Python
Changes:
Version 2022/8 compared to 2021/6 has increased the number of 5 lessons and the duration of 6 minutes. Also, the Quality of the course has increased from 720p to 1080p.
Download link
Download Part 1 – 1 GB
Download Part 2 – 1 GB
Download Part 3 – 1 GB
Download Part 4 – 798 MB
Size
3.79 GB
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