Building a Perceptron From SCRATCH (no frameworks, only math and python) - The Origins of AI - Ep.1

I sure love AI! And there is nothing better than when you learn how something works from absolute scratch. In this video series, I would like you to join me on a journey to the origins of AI and Machine Learning. We are using no frameworks, and in this particular video not even numpy. Just pure math, python and well science really, to explain how AI came to be. There are many forms of machine learning, but neural networks are hands down the most evolved and for sure, mediatic. But before the popular transformers, we had many other types and architectures of machine learning such as CNN, RNN, MLP and of course... the perceptron aka the single artificial neuron or the simplest form of neural network. In this video, we cover the biological science that inspired neural networks, that mathematical functions that make them possible, topics like backpropagation and gradient descent and we do it all from scratch! Hope you enjoy! Source Code on my github - https://github.com/fmiguelmmartins/or... Chapters 00:00 - Intro 01:43 - The Perceptron 02:11 - What is a function 04:50 - Building the perceptron 06:04 - The Weights 08:40 - The Cost Function 10:20 - The Learning Rate 11:16 - Cost Minimization 12:30 - The Bias 15:15 - Optimizing the Weights and Bias 15:48 - Gradient Descent and Backpropagation 23:19 - Outro #neuralnetworks #machinelearning #artificialintelligence