Bloom filters - Eli Bendersky's website

kumar91gopi/Algorithms-and-Data-Structures-in-Ruby: Ruby implementation of Algorithms,Data-structures and programming challenges

Ruby implementation of Algorithms,Data-structures and programming challenges - kumar91gopi/Algorithms-and-Data-Structures-in-Ruby

What are evolutionary algorithms? - Dataconomy

Evolutionary algorithms are optimization techniques inspired by natural evolution, solving complex problems through processes like selection, adaptation, and mutation.

Statistical Formulas For Programmers – Evan Miller

The Pentium contains a complicated circuit to multiply by three

In 1993, Intel released the high-performance Pentium processor, the start of the long-running Pentium line. I've been examining the Pentium'...

calculator-app - Chad Nauseam Home

"A calculator app? Anyone could make that." (this was originally a https://x.com/ChadNauseam/status/1890889465322786878) Not true. A calculator should show you the result of the mathematical expressi…

"A calculator app? Anyone could make that."

Undergraduate Upends a 40-Year-Old Data Science Conjecture | Quanta Magazine

A young computer scientist and two colleagues show that searches within data structures called hash tables can be much faster than previously deemed possible.

Multi-Head Latent Attention and Other KV Cache Tricks

How a Key-Value (KV) cache reduces Transformer inference time by trading memory for computation

Rafael Araujo's 20+ Mesmerizing Geometrical Masterpieces - Abakcus

To celebrate Rafael Araujo's talent and vision, I have curated a selection of his most stunning illustrations, showcasing the elegance and intricacy of his work.

Don't use cosine similarity carelessly - Piotr Migdał

Cosine similarity - the duct tape of AI. Convenient but often misused. Let's find out how to use it better.

Pi in the Pentium: reverse-engineering the constants in its floating-point unit

Intel released the powerful Pentium processor in 1993, establishing a long-running brand of high-performance processors. 1 The Pentium incl...

Note: Based on Ken Shirriff's article "[Pi in the Pentium: reverse-engineering the constants in its floating-point unit](https://www.righto.com/2025/01/pentium-floating-point-ROM.html)", here is an outline of each section with explanations of the findings: | Section | Findings | |---|---| | **Introduction** | The Pentium processor's floating-point unit (FPU) computes transcendental functions like sine…

Massively Speed-Up your Learning Algorithm, with Stochastic Thinning - Machine Learning Techniques

Dramatically Speed-Up your Learning Algorithm, with Stochastic Thinning. Includes use case, Python code, regression and neural network illustrations.

Understanding the BM25 full text search algorithm

BM25 is a widely used algorithm for full text search. I wanted to understand how it works, so here is my attempt at understanding by re-explaining.

can I compare the BM25 scores of documents across multiple queries to determine which query the document best matches?

goal of a full text search algorithm is to take a query and find the most relevant documents

Support Vector Machine (SVM) Algorithm

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are particularly effective when dealing with complex datasets. The core principle…

RNG, PRNG, CSPRNG

A pseudorandom number generator may have good statistical properties but be insecure. But a physical RNG with good statistical properties is probably secure.

crafting interpreters

Shipt’s Pay Algorithm Squeezed Gig Workers. They Fought Back - IEEE Spectru

When their pay suddenly dropped, delivery drivers audited their employer

A Roaringish phrase search algorithm

How phrase search works in search array by intersecting roaring-like numpy arrays.

What AI Engineers Need to Know about Search

All that lexical search context you need to build that RAG app

Understanding and Implementing Genetic Algorithms in Python

Understanding what genetic algorithms are and how they can be implemented in Python.

the Gilbert–Johnson–Keerthi algorithm explained as simply as possible

An Introduction to Post-Quantum Cryptography Algorithms

By Christos Kasparis, EnSilica EETimes (May 15, 2024) The rise of quanum computing paints a significant challenge for the cryptography we rely on today. The modern encryption standards we currently use to safeguard sensitive data and communications, such as DSA, public key RSA…

The Reasonable Effectiveness of the Multiplicative Weights Update Algorithm

papad Hard to believe Sanjeev Arora and his coauthors consider it “a basic tool [that should be] taught to all algorithms students together with divide-and-conquer, dynamic programming, and random sampling.” Christos Papadimitriou calls it “so hard to believe that it has been…

An Introduction to Post-Quantum Cryptography Algorithms

Current encryption methods will likely be broken by 2030. Embedded systems in development now will have a reasonable chance of encountering attacks.

Immersive Math

Index—The Stacks project

an open source textbook and reference work on algebraic geometry

Algorithm Repository

The Kalman Filter

we help students master the Kalman Filter

Uber-style pricing is coming for everything

More and more industries are adopting “dynamic pricing” — and consumers aren’t happy.

A Short Guide to Hard Problems

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape.

Deep Understanding of Garbage Collection: Principles, Algorithms, and Optim

1. Preface Garbage Collection (GC) is an important feature of automatic memory management...

What Is a Schur Decomposition? – Nick Higham

A Schur decomposition of a matrix $latex A\in\mathbb{C}^{n\times n}$ is a factorization $LATEX A = QTQ^*$, where $LATEX Q$ is unitary and $LATEX T$ is upper triangular. The diagonal entries of $LAT…

Kalman Filter Explained Simply - The Kalman Filter

Tired of equations and matrices? Ready to learn the easy way? This post explains the Kalman Filter simply with pictures and examples!

Stop Overusing Scikit-Learn and Try OR-Tools Instead

Many Data Scientists overuse ML and neglect Mathematical Optimisation, even though it’s great for your career and easy to learn

The Perfect Way to Smooth Your Noisy Data

Insanely fast and reliable smoothing and interpolation with the Whittaker-Eilers method.

Market Basket Analysis using Python

In this article, I'll take you through the task of Market Basket Analysis using Python. Market Basket Analysis using Python.

youtube_channel/Python Tutorial Series/fourier_transform1.ipynb at main · lukepolson/youtube_channel

Notebooks for the python tutorials of my youtube channel. See specific youtube video for link to specifc notebook. - lukepolson/youtube_channel

Dictionary of Algorithms and Data Structures

Definitions of algorithms, data structures, and classical Computer Science problems. Some entries have links to implementations and more information.

Graph Embeddings 101: Key Terms Concepts and AI Applications

Research shows knowledge graphs and graph embeddings improve the quality and accuracy of Gen AI responses. Here’s how to get started.

Roundtable

The Algorithms

Open Source resource for learning Data Structures & Algorithms and their implementation in any Programming Language

A non-mathematical introduction to Kalman Filters for programmers

Read my manifesto on Code as an alternative to Mathematics. Code for this article can be found on this Colab Notebook should you choose to follow along. Why Kalman Filters? Kalman filters are ingenius. If you have never heard of them, then a very intuitive (and arguably…

Discovering Differential Equations with Physics-Informed Neural Networks an

A case study with step-by-step code implementation

Similarity Search, Part 4: Hierarchical Navigable Small World (HNSW) | by V

Hierarchical Navigable Small World (HNSW) is a state-of-the-art algorithm used for an approximate search of nearest neighbours. Under the…

Similarity Search, Part 3: Blending Inverted File Index and Product Quantiz

In the first two parts of this series we have discussed two fundamental algorithms in information retrieval: inverted file index and…

Building a Vector Search Engine Using HNSW and Cosine Similarity

Hierarchical Navigable Small World graphs (HNSW) is an algorithm that allows for efficient nearest neighbor search, and the Sentence…

Similarity Search, Part 1: kNN & Inverted File Index

Similarity search is a popular problem where given a query Q we need to find the most similar documents to it among all the documents D.

Similarity Search, Part 2: Product Quantization

Learn a powerful technique to effectively compress large data

Similarity Search, Part 5: Locality Sensitive Hashing (LSH)

Explore how similarity information can be incorporated into hash function

Similarity Search, Part 6: Random Projections with LSH Forest

Understand how to hash data and reflect its similarity by constructing random hyperplanes