Implement Text Auto Completion with LSTM

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Biswanath Halder

1:34:12

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1. Course Overview

1. Course Overview.mp4

01:48

2. Long Short Term Memory Networks (LSTM)

1. Overview.mp4

01:09

2. Introduction to Neural Networks.mp4

05:46

3. Natural Language Text as Sequential Data.mp4

03:32

4. Recurrent Neural Networks (RNNs).mp4

08:14

5. Long Short-term Memory Networks ( LSTMs ).mp4

07:57

6. Networks Architecture Using LSTMs.mp4

05:51

7. Natural Language Generation Using LSTMs.mp4

03:41

8. Summary.mp4

01:13

3. Data Preparation for Assisted Smart Writing

1. Overview.mp4

01:08

2. Explore Enron Email Dataset.mp4

02:46

3. Extract Plaintext Messages from Raw Email Data.mp4

03:15

4. Clean the Email Dataset.mp4

05:44

5. Functions to Preprocess the Dataset.mp4

06:54

6. Preprocess the Email Dataset.mp4

04:05

7. Summary.mp4

00:46

4. Implementation of Auto-completion for Assisted Smart Writing

1. Overview.mp4

01:02

2. Network Architecture for Text Generation.mp4

04:47

3. Tokenization, Vocabulary, and N-grams.mp4

07:10

4. Handle Variable Sentence Lengths.mp4

04:09

5. Predictors and Labels for Training.mp4

02:52

6. Build and Train the Model.mp4

04:20

7. Generate Auto-complete Suggestions.mp4

04:44

8. Summary.mp4

01:19

Description

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.

What You'll Learn?

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.

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Python

Biswanath Halder

Instructor's Courses

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 degree in Computer Science from the Indian Institute of Science, Bangalore, and a Bachelor's degree in Computer Science from Jadavpur University, Kolkata.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.