Dive into a comprehensive 2-hour course on neural networks, designed to be accessible and engaging. Learn to code a neural network from scratch in Python, starting with the basics and progressing to more advanced concepts. Explore the MNIST dataset, understand perceptron models and learning algorithms, and delve into gradient descent and deep learning. Follow along with hands-on coding exercises, covering topics such as multiclass support, simple image processing, and stochastic gradient descent. Access the course code on GitHub and gain practical skills in implementing neural network architectures. By the end of this course, develop a solid foundation in neural network principles and their applications in machine learning.
Overview
Syllabus
Neural Networks For Your Dog - Promo
Neural Networks For Your Dog - 1.1 Introduction
Neural Networks For Your Dog - 2.1 MNIST Dataset
Neural Networks For Your Dog - 2.2 Perceptron Model
Neural Networks For Your Dog - 2.3 Perceptron Learning Algorithm
Neural Networks For Your Dog - 2.4 Pocket Algorithm
Neural Networks For Your Dog - 2.5 Multiclass Support
Neural Networks For Your Dog - 2.6 Perceptron To Neural Network
Neural Networks For Your Dog - 3.1 Simple Images
Neural Networks For Your Dog - 3.2 Random Weights
Neural Networks For Your Dog - 3.3 Gradient Descent
Neural Networks For Your Dog - 3.4 Multiclass Support
Neural Networks For Your Dog - 3.5 Deep Learning
Neural Networks For Your Dog - 3.6 Stochastic Gradient Descent
Neural Networks For Your Dog - 3.7 Going Further
Taught by
GormAnalysis
