Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)
Format
The more copies, the less each one costs
Applied automatically in your cart. No code needed.
Built for school and campus orders
PDF quotes, purchase orders, tax exemption and multi-site delivery, handled by one account manager.
PDF quotes, purchase orders, tax exemption and help with vendor setup.
For schools Make it yoursBookplates, tipped-in pages, belly bands or author signatures. Hardcovers only, subject to publisher approval.
Customization options Ship to every readerOne address, many sites or individual recipients' homes, in the US and abroad.
Fulfillment optionsMachine Learning for Earth Sciences
This textbook introduces the reader to Machine Learning (ML) applications in Earth Sciences. In detail, it starts by describing the basics of machine learning and its potentials in Earth Sciences to solve geological problems. It describes the main Python tools devoted to ML, the typical workflow of ML applications in Earth Sciences, and proceeds with reporting how ML algorithms work. The book provides many examples of ML application to Earth Sciences problems in many fields, such as the clustering and dimensionality reduction in petro-volcanological studies, the clustering of multi-spectral data, well-log data facies classification, and machine learning regression in petrology. Also, the book introduces the basics of parallel computing and how to scale ML models in the cloud. The book is devoted to Earth Scientists, at any level, from students to academics and professionals.
The book, Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment) [Bulk, Wholesale, Quantity] ISBN#9783031351136 in Hardcover by Maurizio Petrelli may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
Details
- Publisher
- Springer International Publishing
- Author
- Maurizio Petrelli
- Format
- Hardcover
- Published
- Sep 23, 2023
- ISBN-13
- 9783031351136
- Pages
- 209
- Printing
- Printed on demand
Machine Learning for Earth Sciences in bulk: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 49 | $87.99 | 12% off list |
| 50 – 99 | $86.99 | 13% off list |
| 100+ | $85.99 | 14% off list |
Popular for
A copy for every student in the class or section.
Shared reading for professional development.
Common reads and first-year programs.
How fast can I get copies of Machine Learning for Earth Sciences?
This title is printed on demand, so it needs production time before it ships. Need them by a specific date? Request a quote and we'll confirm timing before you pay.
Can you ship to several locations or people's homes?
Yes. We ship in bulk to one address, to multiple sites, or to individual recipients, in the US and internationally. See fulfillment options.
Can I get a formal quote for approval before ordering?
Yes. Request a quote and we'll send a PDF you can forward for approval.
Do you accept purchase orders and tax-exempt orders?
Yes. We accept purchase orders upon approval, as well as cards, PayPal, ACH, wire transfers and checks. BookPal is a tax-exempt supplier in all 50 states. See purchase orders and sales tax exemption.
What if I find a lower price?
Send us the link. We match prices from other bulk booksellers and distributors on a new copy in the same edition, available to ship in the quantity you need. Clearance sales and pricing errors are the exception, and we'll tell you quickly if that's the case. Start a price match.
What buyers say
Write a Review
Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment) [9783031351136]
Groups also order
A colleague asked you to approve this order
Your quote list
Add books as you browse, then request one quote for all of them.