Stock photo: cover may vary
Machine Learning and Data Mining for Sports Analytics: 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected ... in Computer and Information Science) Papeback - 2022
by Ulf Brefeld (Editor); Jesse Davis (Editor); Jan Van Haaren (Editor)
- New
A$207.36
A$5.87
Delivery within USA
Standard delivery: 9 to 14 days
More delivery options
Standard delivery: 9 to 14 days
Ships from Cold Books (New York, United States)
Details
- Title Machine Learning and Data Mining for Sports Analytics: 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected ... in Computer and Information Science)
- Author Ulf Brefeld (Editor); Jesse Davis (Editor); Jan Van Haaren (Editor)
- Binding Papeback
- Condition New
- Pages 205
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 1st ed. 2022 edition NO-PA1
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # 6394729732
- ISBN 9783031020438 / 303102043X
- Weight 0.68 lbs (0.31 kg)
- Dimensions 9.21 x 6.14 x 0.46 in (23.39 x 15.60 x 1.17 cm)
- Category Computers - General Information
- Quantity available 4
About Cold Books New York, United States
Reader reviews for Machine Learning and Data Mining for Sports Analytics: 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected ... in Computer and Information Science)
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
