Dive into the world of neural networks with this comprehensive video series that builds a neural network from scratch using Python. Learn the fundamentals of neural network architecture, starting with individual neurons and progressing to full layers. Explore essential concepts such as the dot product, batches, and object-oriented programming in the context of neural networks. Gain a deep understanding of activation functions, including hidden layer activations and the softmax function. Master the implementation of loss calculation using categorical cross-entropy. By the end of this 3.5-hour tutorial, you'll have a solid foundation in neural network development and be able to create your own models from the ground up.
Overview
Syllabus
Neural Networks from Scratch - P.1 Intro and Neuron Code.
Neural Networks from Scratch - P.2 Coding a Layer.
Neural Networks from Scratch - P.3 The Dot Product.
Neural Networks from Scratch - P.4 Batches, Layers, and Objects.
Neural Networks from Scratch - P.5 Hidden Layer Activation Functions.
Neural Networks from Scratch - P.6 Softmax Activation.
Neural Networks from Scratch - P.7 Calculating Loss with Categorical Cross-Entropy.
Neural Networks from Scratch - P.8 Implementing Loss.
Taught by
sentdex
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