A roadmap based on technical understanding of Bitcoin, Ethereum and the lightning network


Understanding how hash functions work

First, what is a hash function?

  • H(1234) = 4.
  • H(12567) = 7.
  • H(127) = 7.
  • H(1111111111) = 1.
  • H(24)=4.
  • H(24)=4.
  • A hash function generates a fixed size output (called digest or hash)
  • For any input…


Super simple, can’t be any easier, code provided

  1. Forward step (where we go from inputs to outputs)
  2. Loss function (where we compare the calculated outputs with real outputs)
  3. Backward step (where we calculate the first delta at the loss function and then back-propagate)
  4. Optimization step (where we update the internal weights with deltas and learning rate)


A part of series about different types of layers in neural networks

Introduction

F(3)=6; F(3)=6; F(3)=6; F(3)=6; F(3)=6; …


A part of series about different types of layers in neural networks

y = f(w*x + b) //(Learn w, and b, with f linear or non-linear activation function)


A part of series about different types of layers in neural networks


The things I learned the hard way as a data scientist

1. You shouldn’t believe it’s magic


The things I learned the hard way as a data scientist

1. You shouldn’t believe it’s magic


Number of features vs number of dimensions


Number of features vs number of dimensions

Assaad MOAWAD

Interested in artificial intelligence, machine learning, neural networks, data science, blockchain, technology, astronomy. Co-founder of Datathings, Luxembourg

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