£113.69

Elsevier Machine Learning for Planetary Science - Research Guide

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Description

As planetary exploration missions generate increasingly large nonlinear datasets, researchers need advanced tools to manage and interpret the information. Machine Learning for Planetary Science provides a practical way to integrate machine learning into your existing research workflow. This book is designed specifically for planetary scientists looking to improve their scientific understanding through modern computational methods. This guide helps you navigate the selection of appropriate methods and tools to solve everyday problems in planetary science. By focusing on real-world applications, the text helps you transition from traditional data analysis to sophisticated machine learning techniques. It serves as a roadmap for handling the complexities of modern space mission data, ensuring you can extract meaningful insights from the vast amounts of information being acquired today.

Key Features

Integrate machine learning methods directly into your current planetary science research workflows.

Learn to handle increasingly large and nonlinear datasets collected from various planetary exploration missions.

Find guidance on selecting the most effective methods and tools for specific scientific problems.

Apply machine learning techniques to enhance your overall scientific understanding of planetary data.

Study practical applications through detailed case studies that demonstrate real-world usage.

Product Specifications

Format
Paperback
Domain
Amazon UK
Release Date
25 March 2022
Listed Since
01 October 2019

Barcode

No barcode data available

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