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Time Complexity: Significance, Types, Algorithms

Knowledge Hut

” In this article, we are going to discuss time complexity of algorithms and how they are significant to us. Nobody would want to use a system which takes a lot of time to process large input size. It defines the way data is arranged in a computer's memory and the operations that can be performed on that data.

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Bring Your Own Algorithm to Anomaly Detection

Pinterest Engineering

It aims to be fast, scalable, and end-to-end: starting from fetching the data from various data sources to be analyzed, and ending with pushing result notifications to tools like Slack. They found the existing selection of anomaly detection algorithms in EGADs to be limiting. What’s the Goal?

Algorithm 106
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Enhancing Distributed System Load Shedding with TCP Congestion Control Algorithm

Zalando Engineering

But our system is event driven, all requests we process are delivered as events via Nakadi. We know if our system runs within its normal limits that we meet our SLOs. If we would control the ingestion of message requests into our system we would be able to process the task in a timely manner.

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Movie Recommendation System: Definition, Strategies, Usecase

Knowledge Hut

Not only could this recommendation system save time browsing through lists of movies, it can also give more personalized results so users don’t feel overwhelmed by too many options. What are Movie Recommendation Systems? Recommender systems have two main categories: content-based & collaborative filtering.

Systems 98
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What are the Commonly Used Machine Learning Algorithms?

Knowledge Hut

Machine Learning is a sub-branch of Artificial Intelligence, used for the analysis of data. It learns from the data that is input and predicts the output from the data rather than being explicitly programmed. There is no end to what can be achieved with the right ML algorithm.

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Scaling the Instagram Explore recommendations system

Engineering at Meta

Explore is one of the largest recommendation systems on Instagram. Using more advanced machine learning models, like Two Towers neural networks, we’ve been able to make the Explore recommendation system even more scalable and flexible. locally popular media), which further contributes to system scalability.

Systems 98
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Interesting startup idea: benchmarking cloud platform pricing

The Pragmatic Engineer

Storing data: data collected is stored to allow for historical comparisons. Benchmarking: for new server types identified – or ones that need an updated benchmark executed to avoid data becoming stale – those instances have a benchmark started on them. Each benchmarking task is evaluated sequentially.

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