Sharing is caring

Here you find a collection of articles on deep learning.

## Deep Learning Foundations

After reading and understanding these posts you should have a basic understanding of neural networks.

- How Do Neural Networks Learn (Forward Propagation)
- Understanding Backpropagation With Gradient Descent
- Neural Network Layers and Architecture
- An Introduction to Neural Network Loss Functions
- Feature Scaling and Data Normalization for Deep Learning
- Weight Decay in Neural Networks
- Dropout Regularization in Neural Networks
- Understanding The Exploding and Vanishing Gradients Problem
- Stochastic Gradient Descent versus Mini Batch Gradient Descent versus Batch Gradient Descent
- Deep Learning Optimization Techniques for Gradient Descent Convergence
- What is Batch Normalization And How Does it Work?

## Deep Learning For Computer Vision

- What is a Convolution: Introducing the Convolution Operation Step by Step
- Understanding Convolutional Filters and Convolutional Kernels
- Understanding Padding and Stride in Convolutional Neural Networks

## Further Resources

For writing these posts I’ve relied on several textbooks, online courses, and blogs.

Sharing is caring