frankturtle Goto Github PK

followers: 13.0 following: 18.0 repos: 59.0 gists: 0.0

Name: frankTurtle.crypto

Type: User

Bio: Software Engineer D_D #6507 Email is actually -> `frank@🐢.kz` but GitHub is too lame to accept it

Twitter: frankturtle__

Location: Long Island, NY

Blog: https://mirror.xyz/frankturtle.eth

Oi, name's frank🐢

I'm an engineer, maker, climate 💛 and overall cool dude 😎.

Occasionally I ✍️ things on Mirror

🐢🦄🚀🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🚀🐢

🦄🐢🦄🚀🐢 Want a mintable NFT of my resume 🦄🚀🦄🚀🐢

🦄🐢🦄🚀🐢 --> OpenSea Resume Collection 🦄🚀🦄🚀🐢

🦄🐢🦄🚀🐢 --> Resume NFT Contract 🦄🚀🦄🚀🐢

🦄🐢🦄🚀🐢 --> Resume NFT Source 🦄🚀🦄🚀🐢

🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🚀🐢

🐢🦄🚀🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🦄🚀🐢🚀🐢

A little more about me 👇👇

const frankTurtle = {
  pronouns: 'he' | 'him' | 'él' ,
  code: ['JS', 'Solidity', 'Java', 'HTML5', 'Tailwind/CSS', 'Python'],
  tools: [IPFS, AWS, Azure, React, Node, NextJS, Docker, Supabase, Ethereum/Polygon],
  architecture: ['microservices', 'TDD', 'scrum', 'CI/CD'],
  communities: {
    tech: {
      member: [D_D, KlimaDAO, IronFish, Toucan, BanklessDAO, MinaProtocol, Praxis],
      founder: [LifeBoss, web3Discord, AskAVet, FormzTo, DYOR.VIP],
    },
    life: ['GivingWhatWeCan.org', 'Cool Earth', 'lichess', 'Fitness', 'Meditation'],
  },
  certs: ['AWS Solutions Architect Associate', 'AWS Cloud Practictioner', 'Azure Fundamentals', 'Scrum Master'],
  challenge: '52 web3 projects each weekend for a year!',
  radicleId: 'hynzgquuyojapj1n4en6zjb4iybn3gp8q169bchmxurgfbgxohw996'
}

Feel free to drop me a message in any of my social channels 🤙🤙

Less trust, more truth

@gavofyork

frankTurtle.crypto's Projects

99-sodas

Bitfountain tutorial using Objective-C - 99 Sodas, using for loops

class-testing-ground

Bitfountain tutorial using Objective-C - Learning about classes and fun stuff :)

dao-job-board

A job board connecting DAOs with talent.

hullabalu

Given a hex-code, convert to normalized floating point, and put into an array

mans-best-friend

Bitfountain tutorial using Objective-C - Mans Best Friend - intro to OOP

Consider the 4-layer back-propogation network. Suppose the network performs logical XOR operation. Neurons 1 and 2 in the input layer accept inputs x1 and x2 respectively and redistribute these inputs to neurons 3 and 4 in the hidden-layer1 without any processing. Neurons 5 and 6 in the hidden-layer2. Neurons 5 and 6 process the inputs from Neurons 3 and 4 and redistrubute to neuron 7 in the output latyer. Now train this ANN network using the larning algorithm, discussed in thie class, with various input epochs 'til the mean square error is less than 0.01. Once the network has solved the problem, test your network, test your network presenting all training sets and calculating the network output. Show your output at various stages.

networkingpacketheader

nodeandexpressfun

Node & Express

frankturtle Goto Github PK

Oi, name's frank🐢

A little more about me 👇👇

frankTurtle.crypto's Projects

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