Deep Learning Tutorials

Welcome to the Deep Learning Tutorials section! Here, you will find a variety of resources to help you learn about deep learning concepts, techniques, and applications.

Overview

Deep learning is a subset of machine learning that structures algorithms in layers to create an "artificial neural network" that can learn and make intelligent decisions on its own.

Key Concepts

• Neural Networks: The basic building blocks of deep learning.
• Activation Functions: Determine whether a neuron should be activated or not.
• Backpropagation: The process of training a neural network by adjusting weights and biases.

Learning Resources

• Introduction to Neural Networks
• Activation Functions Explained

Tutorials

Here are some tutorials to get you started with deep learning:

• Neural Network Basics

  • Neural Network Structure
  • Training a Neural Network

• Convolutional Neural Networks (CNNs)

  • Understanding CNNs
  • Building a CNN

• Recurrent Neural Networks (RNNs)

  • Introduction to RNNs
  • Implementing RNNs

Practice Projects

To solidify your understanding, try out these practice projects:

• Build a Neural Network from Scratch
• Create a CNN for Image Recognition

Neural Network Diagram

Remember, deep learning is a vast field, and these tutorials are just the beginning. Keep exploring and expanding your knowledge!