A Practical Guide to Hybrid Natural Language Processing: Combining Neural Models and Knowledge Graphs for NLP
$23.00
Order Processing Time
All orders placed on our website are processed within 2-4 business days, from Monday to Friday, 8:00 AM – 6:00 PM Pacific Time (PT). Orders received after our daily cut-off time of 10:00 PM PT will be processed on the next business day. Please note that we do not process orders on weekends or public holidays.
Shipping Methods and Carriers
Zetlly partners exclusively with reputable shipping carriers to ensure timely delivery of your orders. We utilize:
-
FedEx
-
UPS
-
USPS
The choice of carrier is determined by factors such as destination, weight, and delivery timeframe to provide optimal service.
Shipping Rates and Fees
-
Free shipping is provided for all orders over $199.
-
Orders under $199 will incur a flat-rate shipping fee of $7.99.
-
All orders shipped within the United States will be subject to a sales tax charge of 5%.
Estimated Delivery Time
Once shipped, orders typically arrive within 6 to 10 business days. Our delivery times are from Monday to Friday, 8:00 AM – 6:00 PM Pacific Time (PT). Please allow additional time for deliveries to remote or rural locations.
Shipping Restrictions
Zetlly currently ships exclusively within the United States. At present, we do not offer international shipping or deliveries to P.O. boxes or APO/FPO addresses. Orders placed with addresses outside our designated delivery areas will be canceled, and refunds will be processed accordingly.
Tracking Your Order
Upon shipment, customers will receive a confirmation email containing tracking information. You can track your order directly through the provided tracking link or by visiting the carrier’s official website:
Please allow up to 48 hours for tracking information to update in the carrier’s system.
Eligibility for Returns and Exchanges
We accept returns and exchanges within 30 days from the date your order is delivered. Items must be unused, in the original condition, and accompanied by the original packaging and receipt or proof of purchase.
How to Return or Exchange an Item
To initiate a return or exchange, please follow these steps:
-
Contact our customer support at contact@zetlly.com with your order number and reason for return or exchange.
-
Our team will respond within 24 hours to provide detailed instructions, including the specific Return Address for your shipment.
-
Package your item securely and include all original packaging and proof of purchase.
Return shipments should be sent to: Blanq LLC 1201 South Hope Street Apt 2413, Los Angeles, CA 90015, USA
Return Conditions
-
Items must be returned in their original condition, unworn, undamaged, and complete with all original packaging and documentation.
-
Items returned without prior authorization or not meeting the above conditions may not qualify for a refund or exchange.
Return Shipping Costs
Customers are responsible for return shipping costs unless the return is due to our error or a defective product. We recommend using a trackable shipping service to ensure your return reaches us safely.
Non-Returnable Items
The following items cannot be returned:
-
Digital products (e-books or downloadable content)
-
Personalized or customized items
-
Gift cards
Accepted Payment Methods
Zetlly accepts the following secure and widely trusted payment options:
-
PayPal: Easily pay through your PayPal account, benefiting from secure transactions and buyer protection.
-
Stripe: Pay securely using major credit and debit cards including Visa, MasterCard, American Express, and Discover via Stripe’s encrypted payment gateway.
Payment Security
At Zetlly, your security is our utmost priority. We utilize advanced encryption technologies and robust security protocols provided by PayPal and Stripe. All payment information entered on our site is encrypted using Secure Socket Layer (SSL) technology, ensuring your financial information remains private and secure throughout the transaction process.
Zetlly does not store any credit card or sensitive financial information directly on our servers, further enhancing the security and protection of your personal data.
Payment Process and Confirmation
Upon placing an order, your chosen payment method (PayPal or Stripe) will immediately process the transaction. You will receive an automated confirmation email shortly after your payment has been successfully completed, detailing your transaction and order summary.
Please retain this confirmation email for your records and reference in case of any inquiries or disputes.
This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs. To this end, it first introduces the main building blocks and then describes how they can be integrated to support the effective implementation of real-world NLP applications. To illustrate the ideas described, the book also includes a comprehensive set of experiments and exercises involving different algorithms over a selection of domains and corpora in various NLP tasks. Throughout, the authors show how to leverage complementary representations stemming from the analysis of unstructured text corpora as well as the entities and relations described explicitly in a knowledge graph, how to integrate such representations, and how to use the resulting features to effectively solve NLP tasks in a range of domains. In addition, the book offers access to executable code with examples, exercises and real-world applications in key domains, like disinformation analysis and machine reading comprehension of scientific literature. All the examples and exercises proposed in the book are available as executable Jupyter not in a Git Hub repository. They are all ready to be run on Google Colaboratory or, if preferred, in a local environment. A valuable resource for anyone interested in the interplay between neural and knowledge-based approaches to NLP, this book is a useful guide for readers with a background in structured knowledge representations as well as those whose main approach to AI is fundamentally based on logic. Further, it will appeal to those whose main background is in the areas of machine and deep learning who are looking for ways to leverage structured knowledge bases to optimize results along the NLP downstream.A Practical Guide to Hybrid Natural Language Processing: Combining Neural Models and Knowledge Graphs for NLP is written by Jose Manuel Gomez-Perez; Ronald Denaux; Andres Garcia-Silva and published by Springer. ISBNs for A Practical Guide to Hybrid Natural Language Processing are 9783030448301, 3030448304 and the print ISBNs are 9783030448295, 3030448290.
Related products
New Book
New Book