This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.
Overview
Syllabus
- Course introduction
- Meet the author
- Course Introduction
- Reading list
- NLP on Google Cloud
- Introduction
- What is NLP?
- NLP history
- NLP architecture
- NLP APIs
- NLP solutions
- Lab introduction: Exploring the Dialogflow API
- Exploring the Dialogflow API
- Summary
- Quiz
- Reading list
- NLP with Vertex AI
- Introduction
- NLP options
- Vertex AI
- NLP with AutoML
- NLP with custom training
- NLP end-to-end workflow
- Lab introduction: Text Classification with AutoML
- Text Classification using AutoML
- Summary
- Quiz
- Reading list
- Text representatation
- Introduction
- Tokenization
- One-hot encoding and bag-of-words
- Word embeddings
- Word2vec
- Transfer learning and reusable embeddings
- Lab introduction: Reusable Embeddings
- Text classification using reusable embeddings
- Summary
- Quiz
- Reading list
- NLP models
- Introduction
- ANN
- TensorFlow
- DNN
- RNN
- LSTM
- GRU
- Lab introduction: Text Classification with Keras
- Keras for Text Classification using Vertex AI
- Summary
- Quiz
- Reading list
- Advanced NLP models
- Introduction
- Encoder-decoder architecture
- Attention mechanism
- Transformer
- BERT
- Large language models
- Lab introduction: Text Translation using Encoder-decoder Architecture
- Encoder decoder
- Summary
- Quiz
- Reading list
- Course summary
- Course Summary
- Your Next Steps
- Course Badge
Tags
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