This course will teach you how to build a system for email auto-completion from scratch using Python and Keras. You’ll learn the internal intricacies of LSTM networks and how they can be used to build systems for the task of text autocompletion.
Have you ever wondered how your favorite messaging app suggests possible next words when you are writing a message or how your email application suggests possible endings of the sentences when you are composing an email? All these are examples of text auto-completion systems which are data-driven systems that assist their users in writing texts. In this course, Implement Text Auto Completion with LSTM, you’ll learn how to build an LSTM-based email auto-completion system from scratch using Python and Keras. First, you’ll learn in detail how LSTM networks work. Next, You’ll discover how LSTMs can be used to build network architectures for various natural language processing tasks and specifically, the task of sentence auto-completion. Finally, you’ll explore an open-source email dataset and build a system for email auto-completion using LSTM networks. By the end of this course you’ll have an in-depth knowledge of text auto-completion systems and the capability of implementing one such system using Python and Keras.
Last Updated 9/2022
Implement Text Auto Completion with LSTM.zip (153.8 MB) | Mirror