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작성자톰아재 조회 96회 작성일 2021-03-09 18:28:49 댓글 0


Algorithms Course - Graph Theory Tutorial from a Google Engineer

This full course provides a complete introduction to Graph Theory algorithms in computer science. Knowledge of how to create and design excellent algorithms is an essential skill required in becoming a great programmer.

You will learn how many important algorithms work. The algorithms are accompanied by working source code in Java to solidify your understanding.


Course created by William Fiset. Check out his YouTube channel:

⭐️ Course Contents ⭐️
⌨️ (0:00:00) Graph Theory Introduction
⌨️ (0:13:53) Problems in Graph Theory
⌨️ (0:23:15) Depth First Search Algorithm
⌨️ (0:33:18) Breadth First Search Algorithm
⌨️ (0:40:27) Breadth First Search grid shortest path
⌨️ (0:56:23) Topological Sort Algorithm
⌨️ (1:09:52) Shortest/Longest path on a Directed Acyclic Graph (DAG)
⌨️ (1:19:34) Dijkstra's Shortest Path Algorithm
⌨️ (1:43:17) Dijkstra's Shortest Path Algorithm | Source Code
⌨️ (1:50:47) Bellman Ford Algorithm
⌨️ (2:05:34) Floyd Warshall All Pairs Shortest Path Algorithm
⌨️ (2:20:54) Floyd Warshall All Pairs Shortest Path Algorithm | Source Code
⌨️ (2:29:19) Bridges and Articulation points Algorithm
⌨️ (2:49:01) Bridges and Articulation points source code
⌨️ (2:57:32) Tarjans Strongly Connected Components algorithm
⌨️ (3:13:56) Tarjans Strongly Connected Components algorithm source code
⌨️ (3:20:12) Travelling Salesman Problem | Dynamic Programming
⌨️ (3:39:59) Travelling Salesman Problem source code | Dynamic Programming
⌨️ (3:52:27) Existence of Eulerian Paths and Circuits
⌨️ (4:01:19) Eulerian Path Algorithm
⌨️ (4:15:47) Eulerian Path Algorithm | Source Code
⌨️ (4:23:00) Prim's Minimum Spanning Tree Algorithm
⌨️ (4:37:05) Eager Prim's Minimum Spanning Tree Algorithm
⌨️ (4:50:38) Eager Prim's Minimum Spanning Tree Algorithm | Source Code
⌨️ (4:58:30) Max Flow Ford Fulkerson | Network Flow
⌨️ (5:11:01) Max Flow Ford Fulkerson | Source Code
⌨️ (5:27:25) Unweighted Bipartite Matching | Network Flow
⌨️ (5:38:11) Mice and Owls problem | Network Flow
⌨️ (5:46:11) Elementary Math problem | Network Flow
⌨️ (5:56:19) Edmonds Karp Algorithm | Network Flow
⌨️ (6:05:18) Edmonds Karp Algorithm | Source Code
⌨️ (6:10:08) Capacity Scaling | Network Flow
⌨️ (6:19:34) Capacity Scaling | Network Flow | Source Code
⌨️ (6:25:04) Dinic's Algorithm | Network Flow
⌨️ (6:36:09) Dinic's Algorithm | Network Flow | Source Code


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The Graph: Why GRT CANNOT Be Ignored!!

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0:00 Intro
2:26 Who Made The Graph?
4:30 What Is The Graph?
8:13 How The Graph Works
11:45 GRT Tokenomics
14:47 The Graph Roadmap
17:48 Final Thoughts


⛓️ Useful Links ⛓️

► The Graph Explorer:
► GRT Token Sale Details:
► The Graph Network:
► How To Create A Subgraph:


Who made The Graph?

The Graph was founded by electrical engineer Yaniv Tal, computer scientist Jannis Pohlmann, and roboticist Brandon Ramirez. When the trio came across Ethereum in 2017, they became obsessed with its potential and started building decentralized applications on the Ethereum blockchain.

However, they noticed a problem. Although Ethereum has a lot of data that is openly accessible to developers, combing through that data is incredibly difficult and this makes it impossible to build more complex dApps without excessive amounts of lag.

They decided to solve this problem by building a data indexing protocol for Ethereum and IPFS that would eventually become known as “The Graph”. An initial whitepaper for the project was written in March 2017, and The Graph was officially announced over a year later in June 2018.

️‍♂‍What Is The Graph?️‍♂‍

The Graph functions as a sort of marketplace for specific data that is on Ethereum. Each dataset on this marketplace is called a ‘subgraph’ and can be seen using The Graph explorer. Each subgraph is basically a description of specific smart contracts within those dApps and any values in them that would be relevant to someone building a new dApp using that data. You think of this as being the equivalent of using bookmarks and a highlighter on a textbook.

How The Graph Works

Using The Graph Explorer, a dApp developer can easily request the data that they need for their dApp using The Graph’s own intuitive querying language called GraphQL. When a data request is made by a developer, nodes on the Graph Network called ‘Indexers’ search through relevant subgraphs to find the information being requested. Indexers choose which subgraphs to pull the data from based on something called a curation signal that is provided by Curators who develop subgraphs and assess them for their quality.

GRT Tokenomics

GRT is an ERC-20 token with an initial supply of 10 billion. Of GRT’s initial supply of 10 billion, only 4% was sold during The Graph’s ICO which took place in October this year. All tokens save for those sold during the ICO are subject to various unlock schedules that last anywhere from 6 months to 10 years. It seems like most of this vesting is set to occur over the next 2 years, with the total amount of GRT tokens in circulations set to triple in just 6 months.

GRT also has an inflation rate of 3% per year which is used to pay Indexing rewards to Indexers. That said, 1% of all query fees go towards burning GRT. The withdrawal tax charged to Curators is also burned, and the same goes for any unclaimed rewards from the Rebate Pool distributed to network participants. This means that GRT could technically become deflationary if there are enough query requests on The Graph Explorer.

The Graph Roadmap

The Graph’s data protocol is being used by developers at Uniswap, Synthetix, Decentraland, Aragon, and many others. Over 3000 subgraphs have been listed on the Graph Explorer so far, and The Graph Network is processing around *half a billion* data queries per day!

The launch of The Graph main net on December 17th ushered in a new era for the project, marking the beginning of a transition to what sounds like a decentralized autonomous organization of DAO. In 2021, The Graph hopes to expand to other blockchains beyond Ethereum. There’s no telling what a protocol like The Graph could do to enhance other smart contract blockchains.



The information contained herein is for informational purposes only. Nothing herein shall be construed to be financial legal or tax advice. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Trading cryptocurrencies poses considerable risk of loss. The speaker does not guarantee any particular outcome.

#TheGraph #GRT #crypto #data #blockchain #ethereum #marketplace #coinbase

Data structures: Introduction to graphs

See complete series on data structures here:

In this lesson, we have described Graph data structure as a mathematical model. We have briefly described the concept of Graph and some of its applications.

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