Named Entity Recognition using LSTMs with Keras

4.4
별점
131개의 평가
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Coursera Project Network
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Build and train a bi-directional LSTM with Keras

Solve the Named Entity Recognition (NER) problem with LSTMs

Clock1.5 hours
Intermediate중급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

In this 1-hour long project-based course, you will use the Keras API with TensorFlow as its backend to build and train a bidirectional LSTM neural network model to recognize named entities in text data. Named entity recognition models can be used to identify mentions of people, locations, organizations, etc. Named entity recognition is not only a standalone tool for information extraction, but it also an invaluable preprocessing step for many downstream natural language processing applications like machine translation, question answering, and text summarization. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

개발할 기술

Deep LearningMachine LearningTensorflowLong Short-Term Memory (ISTM)keras

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  1. Project Overview and Import Modules

  2. Load and Explore the NER Dataset

  3. Retrieve Sentences and Corresponding Tags

  4. Define Mappings between Sentences and Tags

  5. Padding Input Sentences and Creating Train/Test Splits

  6. Build and Compile a Bidirectional LSTM Model

  7. Train the Model

  8. Evaluate Named Entity Recognition Model

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

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NAMED ENTITY RECOGNITION USING LSTMS WITH KERAS의 최상위 리뷰

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