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1
Intro
2
Evolutionary Computation
3
Introduction
4
Why Ships
5
Accidents at Sea
6
Risky Drivers
7
Operational Profiles
8
Data
9
Windward
10
Context
11
What a ship is doing
12
Geography
13
Draft
14
Night
15
Maps
16
Movie
17
Separation Zone
18
Anomaly Detection
19
Weather
20
Operational Profile
21
Accidents Database
22
Machine Learning Models
23
Deep Learning
24
Time Series Data
25
Sentence Completion
26
Time Series
27
Network
28
Predicting Ship Class
29
Predicting Kerch Accident
30
Insurance Companies
31
Lloyds
32
Wayne Ward
33
How do we gain trust
34
How well we become impactful
35
How we do it
36
Probability vs Loss
37
Trust
38
Use
39
SHAP
40
Conclusion
41
Questions
Description:
Explore the cutting-edge application of machine learning in maritime safety through this conference talk from ML Conference 2019. Discover how data science and advanced algorithms are revolutionizing the marine insurance industry, predicting and potentially preventing accidents at sea. Learn about the integration of ship behavior data, including location, speed, maps, and weather information, into sophisticated machine learning models. Gain insights into the challenges of introducing modern technology to a traditional industry and the importance of model interpretability using SHAP. Delve into topics such as evolutionary computation, operational profiles, anomaly detection, and time series analysis in the context of maritime risk assessment. Understand how these innovations can significantly reduce the human, financial, and environmental costs associated with maritime accidents.

Data to the Rescue! Predicting and Preventing Accidents at Sea

MLCon | Machine Learning Conference
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