The Machine Learning Engineer

export default "## The Machine Learning Engineer\n\nAs a Machine Learning Engineer it is your role to build data solutions using a creative approach to solve actual business problems.\n\nAs a Machine Learning Engineer you're continuously moving between three domains:\n\n- Computer Science\n\n  - Software engineering\n  - Best practices\n  - Robustness & resilience\n  - Industrialisation\n\n- Math & Statistics\n\n  - Machine Learning and subdomains like deep learning, computer vision, etc.\n  - Statistics theory & analyses\n  - ELI5'ing how algorithms work\n\n- Business & Domain Expertise\n  - Quickly understand customer's domain\n  - Business challenge understanding\n  - Stakeholder, requirements & scope analysis\n  - Exploratory analysis\n  - Communication of results\n\nThe amount of time one spends in any of these domains depends on the case and customer at hand. Nevertheless being able to navigate these three domains helps you to become an excellent machine learning engineer that can achieve valuable impactful results.\n";

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dataroots
dataroots
data & cloud
data & cloud
artificial intelligence
artificial
intelligence
strategy
strategy