Super Study Guides
Illustrated study guides ideal for visual learners.
algorithms-math
The Future Of Algorithmic Personalization | TechCrunch
Personalization algorithms influence what you’ve chosen yesterday, what you choose today and what you’ll be choosing tomorrow. Simultaneously, there seems to be something wrong with personalization. We are continuously bumping into obtrusive, uninteresting ads. Our digital…
Curation and Algorithms
More and more companies are announcing new products based on human curation, even as the most important content players — Google and Facebook — rely on algorithms. When does curation make sense, an…
The Big Six Matrix Factorizations – Nick Higham
Six matrix factorizations dominate in numerical linear algebra and matrix analysis: for most purposes one of them is sufficient for the task at hand. We summarize them here. For each factorization …
How does Shazam work? Music Recognition Algorithms, Fingerprinting, and Processing | Toptal®
The Shazam music recognition application made it finally possible to put a name to that song on the radio. But how does this magical miracle actually work? In this article, Toptal Freelance Software Engineer Jovan Jovanovic sheds light on the principles of audio signal…
Seriously, stop using RSA | Trail of Bits Blog
Here at Trail of Bits we review a lot of code. From major open source projects to exciting new proprietary software, we’ve seen it all. But one common denominator in all of these systems is that fo…
Bipartite — NetworkX 2.6.2 documentation
Machine Learning Algorithms Cheat Sheet — Accel.AI
Machine learning is a subfield of artificial intelligence (AI) and computer science that focuses on using data and algorithms to mimic the way people learn, progressively improving its accuracy. This way, Machine Learning is one of the most interesting methods in Computer…
Data Scientists, The 5 Graph Algorithms that you should know
Because Graph Analytics is the future
A Primer on Bézier Curves
A detailed explanation of Bézier curves, and how to do the many things that we commonly want to do with them.
3 Reasons Why Data Scientists Should Use LightGBM
There are many great boosting Python libraries for data scientists to reap the benefits of. In this article, the author discusses LightGBM benefits and how they are specific to your data science job.
Visualizing Algorithms
trekhleb/javascript-algorithms: 📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings
📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings - trekhleb/javascript-algorithms
How a Kalman filter works, in pictures | Bzarg
eugeneyan/applied-ml: ? Papers & tech blogs by companies sharing their work
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. - eugeneyan/applied-ml
How Classical Cryptography Will Survive Quantum Computers
Quantum Lab: Scientists are fabricating quantum photonic circuits—consisting of waveguides and other elements—to manipulate single photons for future quantum communications and processing.Oak Ridge National Laboratory / Flickr Nautilus Members enjoy an ad-free experience. Log in…
Efficient matrix multiplication
Efficient matrix multiplication · GitHub
The Floppy Disk of Floating Point
An essay that bids farewell to x87 – a computing architecture too long for this world.
An Introduction to Lagrange Multipliers
Why Disaster Happens at the Edges: An Introduction to Queue Theory – The Ne
What We Talk about When We Talk about Performance.
Curves and Surfaces – Bartosz Ciechanowski
Interactive article explaining how curves and surfaces are modeled.
Python/DIRECTORY.md at master · TheAlgorithms/Python
All Algorithms implemented in Python.
Optimal Estimation Algorithms: Kalman and Particle Filters
An introduction to the Kalman and Particle Filters and their applications in fields such as Robotics and Reinforcement Learning.
Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources
Compendium of free ML reading resources.
[2106.10860v1] Multiplying Matrices Without Multiplying
Multiplying matrices is among the most fundamental and compute-intensive operations in machine learning. Consequently, there has been significant work on efficiently approximating matrix...
10 Computer Vision Terms Everyone Must Know About!
The ten essential computer vision terminologies that everyone should learn to become more proficient at computer vision with sample codes
Complete guide to understanding Node2Vec algorithm
An in-depth guide to understanding node2vec algorithm and its hyper-parameters
Evolution of Search Engines Architecture – Algolia Search Architecture Part
What would a totally new search engine architecture look like? Who better than Julien Lemoine, Co-founder & CTO of Algolia, to describe what the future of search will look like. This is the first article in a series. Search engines, and more generally, information retrieval…
An introduction to A* pathfinding (tutorial)
This is part 3 of a series on bot programming originally published on the Coder One blog. Part 1:...
Python Tricks: Generators Explained
How does a generator in Python work?
Apriori Algorithm for Association Rule Learning — How To Find Clear Links B
Explanation and examples of frequent itemset mining and association rule learning over relational databases in Python
Full Rank Conjoint Analysis
Technique used to gain insights about consumers’ preferences
Poisson's Equation is the Most Powerful Tool not yet in your Toolbox
Poisson's Equation is an incredibly powerful tool...
Types of Correlation Coefficients
Different Kinds of Correlation Coefficients in a Deeper Look
Hands-on Survival Analysis with Python
What companies can learn from employee turnover data
TheAlgorithms/Python: All Algorithms implemented in Python
All Algorithms implemented in Python.
Zero Knowledge
A Not Boring x Jill Carlson Collab on Moon Math, Privacy, and Hype
Introduction to Locality-Sensitive Hashing
A Guide to Genetic ‘Learning’ Algorithms for Optimization
Reconstructing Images using Reinforcement Learning and Genetic Algorithms
Algorithm Tutorial: Intro to Heaps and Priority Queue Implementation
In this edition of the Algorithm Tutorial series, we're going to break down the Heap data structure...
Math Books you should read in 2021
Learn how mathematics influence every aspect of our life.
The Number That Becomes More Amazing the More You Study It
It’s even more astonishing than Dan Brown and Pepsi thought.
Information Theory: A Gentle Introduction
This is the first in a series of articles about Information Theory and its relationship to data driven enterprises and strategy. While…
Data-Technology-Books/dth(157).pdf at master · manjunath5496/Data-Technology-Books
"One person's data is another person's noise." ― K.C. Cole - manjunath5496/Data-Technology-Books
http://algorithmsbook.com/files/dm.pdf
Combinatorial Optimization: The Knapsack Problem
In this story, we are going to discuss an application of dynamic programming techniques to an optimization algorithm. Through the process of developing an optimal solution, we get to study a variety…
Kolmogorov Complexity: Extensions and Applications
https://betterexplained.com/articles/hyperbolic-functions/
Matrix Multiplication Inches Closer to Mythic Goal
A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements.
Graph Theory Basics
What you need to know as graph theory adoption continues to take off