Natural Language Processing on Google Cloud

Google Cloud via Coursera

Coursera based on 534 ratings

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Overview

Natural Language Processing on Google Cloud is a comprehensive, hands-on course designed for developers, data scientists, and AI enthusiasts looking to harness the power of Google Cloud’s NLP tools. This course focuses on building, deploying, and scaling natural language applications using Google Cloud’s AI and machine learning services. Learners begin by exploring the fundamentals of NLP, including text classification, sentiment analysis, entity recognition, and syntax analysis. The course introduces the Cloud Natural Language API, Vertex AI, and AutoML Natural Language, demonstrating...

Syllabus

Course introduction

This module addresses the reasons to learn NLP from Google and provides an overview of the course structure and goals.

NLP on Google Cloud

This module introduces the NLP architecture on Google Cloud. It explores the NLP history, the NLP APIs such as the Dialogflow API, and the NLP solutions such as Contact Center AI and Document AI.

NLP with Vertex AI

This module explores AutoML and custom training, which are the two options to develop an NLP project with Vertex AI. Additionally, the module introduces an end-to-end NLP workflow and provides a hands-on lab to apply the workflow to solve a task of text classification with AutoML.

Text representatation

This module describes the process to prepare text data in NLP and introduces the major categories of text representation techniques.

NLP models

This module describes different NLP models including ANN, DNN, RNN, LSTM, and GRU. It also introduces the benefits and disadvantages of each model.

Advanced NLP models

This module introduces the state-of-the-art technologies and models in NLP: encoder-decoder, attention mechanism, transformers, BERT, and large language models.