What's new
Warez.Ge

This is a sample guest message. Register a free account today to become a member! Once signed in, you'll be able to participate on this site by adding your own topics and posts, as well as connect with other members through your own private inbox!

Implement Text Auto Completion with LSTM

voska89

Moderator
Staff member
Top Poster Of Month
011c2905c7db17217862aa824d93d72f.jpeg

Released 31/08/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning + vtt | Language: English | Duration: 1h 34m | Size: 171.2 MB
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.
Homepage
Code:
https://www.pluralsight.com/courses/implement-text-auto-completion-lstm

Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live ​
Links are Interchangeable - No Password - Single Extraction​
 

Users who are viewing this thread

Back
Top