An architectural pattern is a general, reusable solution to a commonly occurring problem in software architecture within a given context. Architectural patterns are similar to software design pattern but have a broader scope.
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System design is a very broad topic. Even a software engineer with many years of working experience at a top IT company may not be an expert on system design. If you want to become an expert, you need to read many books, articles, and solve real large scale system design problems.
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The Responsible Machine Learning Principles are a practical framework put together by domain experts. Their purpose is to provide guidance for technologists to develop machine learning systems responsibly. Link
Imagine the following scenario: You have a brilliant idea for a new AI project. To make it happen, you need to convince management to fund your idea. You need to pitch your AI project idea to stakeholders and management. Yuck.
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One of the trickiest interview rounds for ML practitioners is ML systems design. If you’re applying to be a Data Scientist, ML Engineer or ML Manager at a big tech company, you’ll probably face an ML Systems design question. I recently tackled this question at a few big tech companies on my way to becoming a Staff ML Engineer at Pinterest. In this article I’m going to talk about how to approach ML Systems Design interviews, core concepts to know and I’ll provide links to some of the resources I used.
The data mesh concept is often presented with scant details regarding an implementation. We have created an opinionated prototype showcasing the principles of data mesh.
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A collection of 245 One Page website templates. Each template includes a review, long screenshot, live demo and download links. These One Page website templates can really help kickstart your next project. Use the top Templates menu to browse sub-categories.
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