The hottest Graphs Substack posts right now

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Why Graphs are great for Fraud Detection [Math Mondays]

Technology Made Simple • 639 implied HN points • 01 Jan 24
🕹 Technology Graphs Neural Networks Machine Learning Data Structures
  1. Graphs are efficient at encoding and representing relationships between entities, making them useful for fraud detection tasks.
  2. Graph Neural Networks excel at fraud detection due to their ability to visualize strong correlations among fraudulent activities that share common properties, adapt to new fraud patterns, and offer transparency in AI systems.
  3. Graph Neural Networks require less labeled data and feature engineering compared to other techniques, have better explainability, and work well with semi-supervised learning, making them a powerful tool for fraud detection.

Edge colourings and Archimedean lattices

A Piece of the Pi: mathematics explained • 24 implied HN points • 18 Feb 24
🔬 Science Mathematics Graphs Symmetry
  1. Edge colorings of graphs are not just recreational, but have practical applications in quantum technology.
  2. Graphs can be colored either by edges or by vertices, with different requirements for each coloring approach.
  3. Vizing's Theorem states that a graph can be edge colored with either the maximum degree or the maximum degree plus one colors.

Novaxia vs Bigpharmia

Logging the World • 199 implied HN points • 04 Nov 22
🔬 Science Health Graphs Vaccines Modeling Data Analysis
  1. Understand the impact of vaccines on disease spread: Novaxia and Bigpharmia are examples of two scenarios showing how vaccines can affect the spread of a disease differently.
  2. Graphs help visualize data trends: Using different types of graphs can show how disease spread changes over time and the effectiveness of interventions like vaccines.
  3. Consider the importance of logarithmic scales: Logarithmic scales can provide a different perspective on data trends, allowing for better understanding of the impact of interventions like vaccines.
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[Solution]Problem 76: Combination Sum [Google]

Technology Made Simple • 59 implied HN points • 24 Feb 23
🕹 Technology Programming Algorithms Graphs Recursion Backtracking
  1. The problem involves backtracking, recursion, and graph modeling to find unique combinations that sum to a target.
  2. Modeling the problem as a graph with states and transitions helps in traversal mechanics using DFS.
  3. Implementing a simple graph traversal algorithm, backtracking, and a global variable to track combinations can efficiently solve the problem.

[Solution]Problem 72: Permutation in String [Amazon]

Technology Made Simple • 39 implied HN points • 27 Jan 23
🕹 Technology Algorithms Binary Trees Graphs Coding Data Structures
  1. The problem discussed is about validating a binary search tree, ensuring the left subtree contains smaller values, the right subtree contains greater values, and both are valid binary search trees.
  2. Examples are provided to illustrate the concept, showing a valid and an invalid binary search tree.
  3. Constraints include the number of nodes and the value ranges in the tree.

[Solution]Problem 50:Rotting Oranges[Microsoft]

Technology Made Simple • 59 implied HN points • 04 Aug 22
🕹 Technology Coding Graphs Problem Solving Programming
  1. The problem of rotting oranges involves graph theory and BFS algorithms, and it can be challenging due to multiple oranges rotting simultaneously.
  2. The goal is to find the minimum number of minutes required for all fresh oranges to rot. If impossible, return -1.
  3. Understanding the problem thoroughly and having a structured approach to solving it is essential in coding interviews.

How to Figure out the correct distance finding algorithm [Technique Tuesday]

Technology Made Simple • 79 implied HN points • 30 Mar 22
🕹 Technology Algorithm Graphs Coding Interviews Data Structures
  1. BFS and DFS algorithms are foundational and crucial for various graph traversal problems, forming the basis for more complicated algorithms.
  2. Topological Sort, Djikstra's Algorithm, and A* are important graph traversal algorithms to master, especially for weighted graphs and AI applications like self-driving cars.
  3. For determining the correct graph traversal algorithm, identify if you need to find the shortest path (use BFS or A* for unweighted/weighted graphs), or if you need to visit the complete graph (use DFS for problems involving the entire graph).

All about the graphs [Math Monday]

Technology Made Simple • 59 implied HN points • 29 Mar 22
🕹 Technology Data Structures Algorithms Graphs Coding Interviews
  1. Graphs can be seen from various perspectives: charts and plots (stats), maps with complex algorithms (graph theory), and adjacency lists for coding. Understanding these perspectives is crucial for effective use of graphs.
  2. Identifying whether a problem could be a graph problem involves recognizing the entities (nodes), relationships (edges), and weights in the context of a system. This spotting framework helps in solving graph-related problems efficiently.
  3. Practicing graph spotting as a skill involves starting with easy problems to identify graph components quickly. Familiarity with graphs and the ability to spot them easily is crucial for solving graph problems in interviews.

[Solution]Problem 37: Word Search[Amazon]

Technology Made Simple • 39 implied HN points • 13 May 22
🕹 Technology Coding Graphs Backtracking Algorithms
  1. Identifying the pattern in graph problems can help simplify the solution - like finding adjacent letters in a grid.
  2. Using the correct graph traversal algorithm is crucial, like choosing DFS for visiting every node in a graph.
  3. Implementing backtracking in DFS can help efficiently solve problems - like removing unnecessary nodes for optimization.

[Solution]Problem 34: Find Safe States[Microsoft]

Technology Made Simple • 39 implied HN points • 22 Apr 22
🕹 Technology Graphs DFS Algorithm Coding Programming
  1. The problem involves identifying safe nodes in a directed graph, which are nodes where all paths lead to terminal nodes. These safe nodes cannot be part of a cycle.
  2. The algorithm for identifying safe nodes can utilize DFS (Depth First Search) to traverse the graph efficiently and detect cycles or terminal nodes.
  3. Traversing the graph step-by-step, checking if each node is safe based on its neighbors, and building the solution methodically is key to solving the problem effectively.

[Solution]Problem 33: Number of Islands[Spotify]

Technology Made Simple • 39 implied HN points • 15 Apr 22
🕹 Technology Graphs DFS
  1. Understanding the structure of a problem is crucial for developing an efficient solution. Recognizing familiar patterns can guide the approach.
  2. Graph traversal in problems like these can often be approached using either Breadth-First Search (BFS) or Depth-First Search (DFS). In this case, both algorithms are applicable.
  3. Implementing a visited set in algorithms like DFS or BFS can prevent repeated work and infinite loops, leading to a more efficient solution.

[Solution]Problem 30: Find Distance to nearest Exit[Google]

Technology Made Simple • 39 implied HN points • 25 Mar 22
🕹 Technology Programming Algorithms Graphs
  1. Google coding challenges can be tricky and often require exploring optimal solutions beyond the obvious
  2. When solving problems involving distances in grids, consider using the concept of Manhattan Distance and graph structures to represent relationships between objects
  3. Choosing the best graph traversal algorithm is crucial; in cases like this problem where distances are equal and not weighted, BFS can be a simpler and more suitable choice compared to more complex algorithms like DFS

Problem 37: Word Search[Amazon]

Technology Made Simple • 19 implied HN points • 12 May 22
🕹 Technology Backtracking Recursion Strings Graphs
  1. Next week's topic will introduce the concept of a Recursive Leap of Faith to help with backtracking, dynamic programming, and recursion.
  2. You can test your coding skills with a popular interview question: Leetcode 79. Word Search.
  3. Ensure your code passes Leetcode submissions even if it doesn't match top speeds, and focus on understanding the problem and providing a correct solution.