This 1-hour-long project-based course will teach you how to use Keras API with TensorFlow to build and train a bidirectional neural network model for LSTM recognition of named entities in text data. Named entity recognition models can be used for identifying mentions of people, places, organizations, etc. Named entity recognition can be used as a standalone tool to extract information, but it is also a valuable preprocessing step for many downstream natural-language processing applications such as machine translation, question answering, text summarization, and question answering. Coursera's Rhyme project platform allows you to do this course hands-on. Rhyme allows you to work in a browser-based manner on projects. Instant access to pre-configured cloud desktops that contain all the software and data needed for your project will be available. Everything is already configured in your internet browser, so you can focus on learning. You'll have instant access to the cloud desktop with Python, Jupyter and Keras installed for this project. Notes: You can access the cloud desktop five times. However, you can access the instructions videos as many times you wish. This course is best for learners who live in the North America region. We are currently working to offer the same experience in other areas.
