Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
TensorFlow Deep Learning Projects

You're reading from   TensorFlow Deep Learning Projects 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning

Arrow left icon
Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788398060
Length 320 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Authors (5):
Arrow left icon
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Abhishek Thakur Abhishek Thakur
Author Profile Icon Abhishek Thakur
Abhishek Thakur
Alexey Grigorev Alexey Grigorev
Author Profile Icon Alexey Grigorev
Alexey Grigorev
+1 more Show less
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Recognizing traffic signs using Convnets 2. Annotating Images with Object Detection API FREE CHAPTER 3. Caption Generation for Images 4. Building GANs for Conditional Image Creation 5. Stock Price Prediction with LSTM 6. Create and Train Machine Translation Systems 7. Train and Set up a Chatbot, Able to Discuss Like a Human 8. Detecting Duplicate Quora Questions 9. Building a TensorFlow Recommender System 10. Video Games by Reinforcement Learning 11. Other Books You May Enjoy

Creating fuzzy features

The next set of features are based on fuzzy string matching. Fuzzy string matching is also known as approximate string matching and is the process of finding strings that approximately match a given pattern. The closeness of a match is defined by the number of primitive operations necessary to convert the string into an exact match. These primitive operations include insertion (to insert a character at a given position), deletion (to delete a particular character), and substitution (to replace a character with a new one).

Fuzzy string matching is typically used for spell checking, plagiarism detection, DNA sequence matching, spam filtering, and so on and it is part of the larger family of edit distances, distances based on the idea that a string can be transformed into another one. It is frequently used in natural language processing and other applications...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image