Yue Zhang,Zhiyang Teng
Natural Language Processing: A Machine Learning Perspective
Natural Language Processing: A Machine Learning Perspective
💎 Earn 276 Points (£2.76) on this item.
YOU SAVE £2.79
- Condition: Brand new
- UK Delivery times: Usually arrives within 2 - 3 working days
- UK Shipping: Fee starts at £2.39. Subject to product weight & dimension
Bulk ordering. Want 15 or more copies? Get a personalised quote and bigger discounts. Learn more about bulk orders.
Couldn't load pickup availability
- More about Natural Language Processing: A Machine Learning Perspective
Format: Hardback
Length: 484 pages
Publication date: 07 January 2021
Publisher: Cambridge University Press
With a machine learning approach and less focus on linguistic details, this natural language processing textbook introduces the fundamental mathematical and deep learning models for NLP in a unified framework. An invaluable, accessible and up-to-date tool for the upper undergraduate and graduate student, with sample code available online.
Weight: 1184g
Dimension: 196 x 253 x 28 (mm)
ISBN-13: 9781108420211
This item can be found in:
UK and International shipping information
UK and International shipping information
UK Delivery and returns information:
- Delivery within 2 - 3 days when ordering in the UK.
- Shipping fee for UK customers from £2.39. Fully tracked shipping service available.
- Returns policy: Return within 30 days of receipt for full refund.
International deliveries:
Shulph Ink now ships to Australia, Belgium, Canada, France, Germany, Ireland, Italy, India, Luxembourg Saudi Arabia, Singapore, Spain, Netherlands, New Zealand, United Arab Emirates, United States of America.
- Delivery times: within 5 - 10 days for international orders.
- Shipping fee: charges vary for overseas orders. Only tracked services are available for most international orders. Some countries have untracked shipping options.
- Customs charges: If ordering to addresses outside the United Kingdom, you may or may not incur additional customs and duties fees during local delivery.
