MACHINE LEARNING
A
mazon Web Services ( AWS ) has established itself as a pioneering force in cloud computing and machine learning , transforming how businesses leverage artificial intelligence ( AI ) and ML technologies .
The company ’ s journey in machine learning began with the launch of its first ML service in 2015 , and it has since built a comprehensive ecosystem that powers innovation across industries , particularly in finance and fintech .
Foundational Developments and Key Milestones AWS ’ s machine learning leadership emerged from its early recognition that ML would become crucial for business transformation .
In 2015 , the company introduced Amazon Machine Learning , providing developers with tools to build predictive applications .
However , the real breakthrough came in 2017 with the launch of Amazon SageMaker , a fully managed service that revolutionised how developers and data scientists build , train and deploy ML models at scale .
Several key milestones mark AWS ’ s evolution in machine learning . In 2018 , AWS introduced SageMaker Ground Truth for data labelling and Amazon Personalise for real-time personalisation and recommendations .
The company strengthened its position in 2019 with Amazon Forecast , bringing timeseries forecasting capabilities to businesses without requiring deep ML expertise .
The introduction of Amazon CodeGuru in 2020 showcased AWS ’ s ability to apply ML
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