Machine Learning and Deep Learning – A review for Ecologists

04/11/2022
by   Maximilian Pichler, et al.
6

The popularity of Machine learning (ML), Deep learning (DL), and Artificial intelligence (AI) has sharply risen in recent years. Despite their spike in popularity, the inner workings of ML and DL algorithms are perceived as opaque, and their relationship to classical data analysis tools remains debated. It is often assumed that ML and DL excel primarily at making predictions. Recently, however, they have been increasingly used for classical analytical tasks traditionally covered by statistical models. Moreover, recent reviews on ML have focused exclusively on DL, missing out on synthesizing the wealth of ML algorithms with different advantages and general principles. Here, we provide a comprehensive overview of ML and DL, starting with their historical developments, their algorithm families, their differences from traditional statistical tools, and universal ML principles. We then discuss why and when ML and DL excel at prediction tasks, and where they could offer alternatives to traditional statistical methods for inference, highlighting current and emerging applications for ecological problems. Finally, we summarize emerging trends, particularly scientific and causal ML, explainable AI, and responsible AI that may significantly impact ecological data analysis in the future.

READ FULL TEXT

page 12

page 14

page 15

page 21

research
07/17/2019

Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods

The ever-growing big data and emerging artificial intelligence (AI) dema...
research
10/13/2022

Machine Learning vs. Deep Learning in 5G Networks – A Comparison of Scientific Impact

Introduction of fifth generation (5G) wireless network technology has ma...
research
05/19/2022

Deep Learning in Business Analytics: A Clash of Expectations and Reality

Our fast-paced digital economy shaped by global competition requires inc...
research
09/08/2022

Dr. Neurosymbolic, or: How I Learned to Stop Worrying and Accept Statistics

The symbolic AI community is increasingly trying to embrace machine lear...
research
06/18/2023

Can predictive models be used for causal inference?

Supervised machine learning (ML) and deep learning (DL) algorithms excel...
research
04/30/2020

The Information Bottleneck Problem and Its Applications in Machine Learning

Inference capabilities of machine learning (ML) systems skyrocketed in r...
research
01/16/2020

Engineering AI Systems: A Research Agenda

Deploying machine-, and in particular deep-learning, (ML/DL) solutions i...

Please sign up or login with your details

Forgot password? Click here to reset