TIME Magazine's 100 Most Influential People of 2023 includes three courageous and inspiring Iranians. Note that these resources will only help you dip your toes into the water.ĭeeper expertise in ML systems requires (1) reading technology blogs from tech companies, (2) reviewing arXiv papers on your topic of interest, and off course (3) getting your hands dirty designing and deploying ML systems. These four resources should cover most of the components and design patterns you would encounter in tech, especially if you work on recommender systems. One of the most common questions I get from my mentees is: "How do I learn about designing ML systems?"ġ- For a comprehensive understanding of the different components of an ML system, I recommend "ML Design Pattern" by Valliappa LakshmananĢ- For a review of ML stacks at different tech companies, I recommend "ML System Design Interview" by Ali Aminianģ- For a high-level summary of ML systems, check out ApplyingML by Eugene Yan.Ĥ- Tensorflow Recommender Systems Tutorial for a shallow hands-on experience on how recommender systems work.
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