Description
Natural Language Processing with Transformers in Python is a course on learning natural language processing with transformers using tools from 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 with Transformers in Python:
- Industry standard for natural language processing using Transformer models
- Build Complete Models of Question-Answer Transformers
- Perform Emotion Analysis with Transformer Models Using PyTorch and TensorFlow
- Advanced search technology like Elasticsearch and Facebook Match Search Artificial Intelligence (FAISS)
- Measure the effectiveness of language models using advanced metrics like ROUGE
- Technology for manufacturing vectors such as BM25 or dense passage recuperators (DPR)
- An overview of recent advances in natural language processing
- Understanding Attention and Other Key Components of Transformers
- Text Data Preprocessing for NLP
Course specifications
Publisher: Udemy
Instructors: James Briggs
French language
Level: Advanced to Advanced
Number of lessons: 99
Duration: 11 hours and 24 minutes
Course topics:
Course prerequisites:
Data science experience an asset
Pictures
sample movie
Installation guide
After ripping, watch with your favorite player.
english subtitle
Quality: 720p
Download link
File password(s): ngaur.com
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3.1 GB