Step-by-Step Guide to Navigate AWS GameDay — Finding Monoceros
<h2>About AWS GameDay</h2>
<p>AWS GameDay offers an exciting and interactive learning opportunity that replicates real-world scenarios within the AWS (Amazon Web Services) ecosystem. During a GameDay event, teams, typically comprising 1 to 4 members, embark on a journey to tackle challenges across various domains, including security, sustainability, MLOps, cost optimization, and more.</p>
<h2>My Role</h2>
<p>In our team of three, each of us embraced specific roles. As the data scientist within the team, I undertook the responsibility of constructing an AutoGluon classifier to predict Monoceros stars using the provided data. Additionally, I crafted a machine learning pipeline designed to automate data preprocessing, model training, evaluation, and model registration.</p>
<h2>Key Learnings</h2>
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<li>Collaboration is the cornerstone of success, and while this may sound like a well-worn adage, it holds profound significance in the ever-evolving technology landscape. Although we are often enticed by tales of solitary pioneers in IT, the truth is that to deliver impactful solutions at scale, we must come together as a team. Teamwork not only allows each member to concentrate on their specialized domain but also infuses us with the vigor to remain focused.</li>
<li>Coming from a non-tech background, my prior experience was primarily confined to predicting Houston house prices, a project well-known in the realm of data science. However, I firmly believe that true learning stems from active engagement and the quest to ask the right questions, rather than having all the answers. Whether you’re seeking a transition from a non-tech to tech role, progressing from a data science/analyst role to that of a machine learning engineer, or enhancing your team’s data capabilities, I present to you my personalized <em>Dynamic Insight and Development (DID) Framework</em>:</li>
</ul>
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