Learning to Love Data Science: Explorations of Emerging Technologies and Platforms for Predictive Analytics, Machine Learning, Digital Manufacturing and Supply Chain Optimization Paperback - 2015 - 1st Edition
by Barlow, Mike
- Used
- very good
- first
A$10.83
Free Delivery within USA
Standard delivery: 7 to 14 days
More delivery options
Standard delivery: 7 to 14 days
Ships from BooksRun (Pennsylvania, United States)
Details
- Title Learning to Love Data Science: Explorations of Emerging Technologies and Platforms for Predictive Analytics, Machine Learning, Digital Manufacturing and Supply Chain Optimization
- Author Barlow, Mike
- Binding Paperback
- Edition number 1st
- Edition 1
- Condition Used - Very good
- Pages 159
- Volumes 1
- Language ENG
- Publisher O'Reilly Media
- Publication date 2015-12-15
- Features Bibliography
- Bookseller's Inventory # 1491936584-11-1
- ISBN 9781491936580 / 1491936584
- Weight 0.5 lbs (0.23 kg)
- Dimensions 9 x 6 x 0.3 in (22.86 x 15.24 x 0.76 cm)
- Category Computers - Data Base Management
- Library of Congress subjects Data mining, Machine learning
- Dewey Decimal Code 006.312
- Quantity available 1
About BooksRun Pennsylvania, United States
Specialising in: Textbooks
Biblio member since 2016
BooksRun - best place to buy, sell or rent cheap textbooks
30 days return guarantee. 10% restocking fee applies to discretionary returns
Reader reviews for Learning to Love Data Science: Explorations of Emerging Technologies and Platforms for Predictive Analytics, Machine Learning, Digital Manufacturing and Supply Chain Optimization
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