Play all

How Convolution Works

The Softmax neural network layer

Batch normalization

Build a 2D convolutional neural network, part 1: Getting started

Build a 2D convolutional neural network, part 2: Overview

Build a 2D convolutional neural network, part 3: MNIST digits

Build a 2D convolutional neural network, part 4: Model overview

Build a 2D convolutional neural network, part 5: Pre-trained model results

Build a 2D convolutional neural network, part 6: Examples of successes and failures

Build a 2D convolutional neural network, part 7: Why Cottonwood?

Build a 2D convolutional neural network, part 8: Training code setup

Build a 2D convolutional neural network, part 9: Adding layers

Build a 2D convolutional neural network, part 10: Connecting layers

Build a 2D convolutional neural network, part 11: The training loop

Build a 2D convolutional neural network, part 12: Testing loop

Build a 2D convolutional neural network, part 13: Loss history and text summary

Build a 2D convolutional neural network, part 14: Collecting examples

Build a 2D convolutional neural network, part 15: Rendering examples

Build a 2D convolutional neural network, part 16: Cottonwood code tour

Build a 2D convolutional neural network, part 17: Cottonwood cheatsheet

Description:

Dive into a comprehensive 2.5-hour tutorial on two-dimensional convolution and convolutional neural networks. Learn the fundamentals of convolution operations, explore the Softmax neural network layer, and understand batch normalization. Build a 2D convolutional neural network from scratch, starting with the basics and progressing through a step-by-step implementation using the MNIST digits dataset. Gain insights into model architecture, pre-trained model results, and analyze examples of successes and failures. Discover the advantages of using Cottonwood framework, set up training code, add and connect layers, and implement training and testing loops. Explore loss history visualization, text summaries, and learn how to collect and render examples. Conclude with a Cottonwood code tour and a handy cheatsheet for quick reference.

Convolution in Two Dimensions

Add to list

#Computer Science #Artificial Intelligence #Neural Networks #Deep Learning #Computer Vision #Batch Normalization

0:00 / 0:00