Elements of computer science

Utilizing Bloom filters for efficient querying in large-scale datasets - Part 4
Feb 13, 2025 · 5 min read ·
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In this post, we will provide an informal introduction to Bloom filters using a simple analogy with a stamp collection.
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Utilizing Bloom filters for efficient querying in large-scale datasets - Part 3
Feb 13, 2025 · 2 min read ·
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In this post, we will briefly explore a concrete example where the techniques mentioned earlier fall short of fully addressing the problem. We will then discuss why a new solution is required.
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Utilizing Bloom filters for efficient querying in large-scale datasets - Part 2
Feb 13, 2025 · 6 min read ·
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In this post, we will explore various techniques for storing and querying massive amounts of data, with a particular emphasis on hashing.
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Utilizing Bloom filters for efficient querying in large-scale datasets - Part 1
Feb 13, 2025 · 2 min read ·
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Starting today, we are introducing a series on using Bloom filters for efficiently determining the existence of elements in large datasets. Our objective is to provide a comprehensive overview, exploring their necessity for scalable querying, analyzing their time complexity, and demonstrating a simple implementation in …
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Implementing the Google's autocomplete feature with ngram language models - Part 6
Jan 8, 2025 · 4 min read ·
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In this final post, we will briefly examine the strengths and weaknesses of n-gram models and explore why it may be necessary to refine them for improved predictions.
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Implementing the Google's autocomplete feature with ngram language models - Part 5
Jan 8, 2025 · 6 min read ·
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In this post, we will implement a simple n-gram model in C# using a limited corpus. This will highlight the key considerations to keep in mind when it comes to coding.
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Implementing the Google's autocomplete feature with ngram language models - Part 4
Jan 8, 2025 · 7 min read ·
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In this post, we will build on the concepts covered in the previous posts and explore how they can be applied to n-gram language models.
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Implementing the Google's autocomplete feature with ngram language models - Part 3
Jan 8, 2025 · 6 min read ·
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In this post, we will delve into the concept of probabilities, with a particular emphasis on conditional probabilities. This foundational understanding will prepare us for the next post, where we will explore n-gram language models in greater depth.
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Implementing the Google's autocomplete feature with ngram language models - Part 2
Jan 8, 2025 · 2 min read ·
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In this post, we provide a brief overview of the Google's autocomplete feature to showcase a concrete application of the concepts we are exploring.
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Implementing the Google's autocomplete feature with ngram language models - Part 1
Jan 8, 2025 · 2 min read ·
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Starting today, we launch a series of articles delving into the implementation of the Google's autocomplete feature (we will detail later what it is exactly). More broadly, our aim is to explore the n-gram language model, shedding light on how to predict and generate sentence endings based on their beginnings. Our goal …
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