Media Summary: As financial institutions adopt AI/ML, the regulatory requirements are mandating explainability of the machine learning models. In American football, players can sustain head impacts during play, but the accumulated effect of these impacts to players' health ... Join this keynote to be inspired by Tom Taylor, SVP of

Amazon Re Mars 2022 Improve - Detailed Analysis & Overview

As financial institutions adopt AI/ML, the regulatory requirements are mandating explainability of the machine learning models. In American football, players can sustain head impacts during play, but the accumulated effect of these impacts to players' health ... Join this keynote to be inspired by Tom Taylor, SVP of Agriculture is one of the least digitized industries. Every year, there are trillions of pieces of fruit picked by hand. Farmers ... Robotics innovation is moving at a rapid pace. That's why it's critical for robotics companies to accelerate and scale their hardware ... Computer vision (CV) algorithms process and analyze visual data to detect objects and classify images in ways that mimic the ...

Developers often find themselves spending significant time searching for documentation and code samples instead of focusing on ... In a changing global environment, land and natural resource markets require consistent data spanning from local actions to global ... The frequency and severity of natural disasters are Join this session to learn about the mathematics that provide the foundation for machine learning, unification of various machine ... In this session, learn how AWS and BMW collaborate to solve robot trajectory planning problems at industry-relevant scale. Building and training of ML workloads can be an energy-intensive process, and high accuracy and large computational resources ...

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Amazon re:MARS 2022 - Improve explainability of ML models to meet regulatory requirements (MLR319)
Amazon re:MARS 2022 - Using machine learning to improve player safety in the NFL (MLR323)
Amazon re:MARS 2022 - Day 1 - Keynote
Amazon re:MARS 2022 - Feeding the future with autonomous agriculture (ROB221-L)
Amazon re:MARS 2022 - How small robotics teams innovate and scale quickly (ROB213)
Amazon re:MARS 2022 - Creating high-quality training sets for machine learning models (ROB225)
Amazon re:MARS 2022 - The future of software development, powered by machine learning (MLR225)
Amazon re:MARS 2022 Highlights | Amazon News
Amazon re:MARS 2022 - Taking the planet’s pulse: AI to empower adaptation to global change (MLR219)
Amazon re:MARS 2022 - Improving disaster response with machine learning (MLR216)
Amazon re:MARS 2022 - The mathematics of machine learning (MLR325)
Amazon re:MARS 2022 - Robot trajectory planning with hybrid quantum algorithms (MLR317)
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Amazon re:MARS 2022 - Improve explainability of ML models to meet regulatory requirements (MLR319)

Amazon re:MARS 2022 - Improve explainability of ML models to meet regulatory requirements (MLR319)

As financial institutions adopt AI/ML, the regulatory requirements are mandating explainability of the machine learning models.

Amazon re:MARS 2022 - Using machine learning to improve player safety in the NFL (MLR323)

Amazon re:MARS 2022 - Using machine learning to improve player safety in the NFL (MLR323)

In American football, players can sustain head impacts during play, but the accumulated effect of these impacts to players' health ...

Amazon re:MARS 2022 - Day 1 - Keynote

Amazon re:MARS 2022 - Day 1 - Keynote

Join this keynote to be inspired by Tom Taylor, SVP of

Amazon re:MARS 2022 - Feeding the future with autonomous agriculture (ROB221-L)

Amazon re:MARS 2022 - Feeding the future with autonomous agriculture (ROB221-L)

Agriculture is one of the least digitized industries. Every year, there are trillions of pieces of fruit picked by hand. Farmers ...

Amazon re:MARS 2022 - How small robotics teams innovate and scale quickly (ROB213)

Amazon re:MARS 2022 - How small robotics teams innovate and scale quickly (ROB213)

Robotics innovation is moving at a rapid pace. That's why it's critical for robotics companies to accelerate and scale their hardware ...

Amazon re:MARS 2022 - Creating high-quality training sets for machine learning models (ROB225)

Amazon re:MARS 2022 - Creating high-quality training sets for machine learning models (ROB225)

Computer vision (CV) algorithms process and analyze visual data to detect objects and classify images in ways that mimic the ...

Amazon re:MARS 2022 - The future of software development, powered by machine learning (MLR225)

Amazon re:MARS 2022 - The future of software development, powered by machine learning (MLR225)

Developers often find themselves spending significant time searching for documentation and code samples instead of focusing on ...

Amazon re:MARS 2022 Highlights | Amazon News

Amazon re:MARS 2022 Highlights | Amazon News

Amazon re

Amazon re:MARS 2022 - Taking the planet’s pulse: AI to empower adaptation to global change (MLR219)

Amazon re:MARS 2022 - Taking the planet’s pulse: AI to empower adaptation to global change (MLR219)

In a changing global environment, land and natural resource markets require consistent data spanning from local actions to global ...

Amazon re:MARS 2022 - Improving disaster response with machine learning (MLR216)

Amazon re:MARS 2022 - Improving disaster response with machine learning (MLR216)

The frequency and severity of natural disasters are

Amazon re:MARS 2022 - The mathematics of machine learning (MLR325)

Amazon re:MARS 2022 - The mathematics of machine learning (MLR325)

Join this session to learn about the mathematics that provide the foundation for machine learning, unification of various machine ...

Amazon re:MARS 2022 - Robot trajectory planning with hybrid quantum algorithms (MLR317)

Amazon re:MARS 2022 - Robot trajectory planning with hybrid quantum algorithms (MLR317)

In this session, learn how AWS and BMW collaborate to solve robot trajectory planning problems at industry-relevant scale.

Amazon re:MARS 2022 - Optimizing AI/ML workloads for sustainability (MLR315)

Amazon re:MARS 2022 - Optimizing AI/ML workloads for sustainability (MLR315)

Building and training of ML workloads can be an energy-intensive process, and high accuracy and large computational resources ...