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.
Author Name: Biswanath Halder
Author Description:
Biswanath is a Data Scientist who has around nine years of working experience in companies like Oracle, Microsoft, and Adobe. He has extensive knowledge of Machine Learning, Deep Learning, and Reinforcement Learning. He specializes in applying Machine Learning and Deep Learning techniques in complex business applications related to computer vision and natural language processing. He is also a freelance educator and teaches Statistics, Mathematics, and Machine Learning. He holds a Master’s degre… more