Welcome to the basics of Deep Learning! This page will provide an overview of the fundamental concepts, techniques, and applications of deep learning.
What is Deep Learning?
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 Components
- Neural Networks: The building blocks of deep learning, inspired by the human brain.
- Layers: Input, hidden, and output layers that process information.
- Activations: Functions that determine the output of each neuron.
- Backpropagation: An algorithm that adjusts the weights and biases of the network to improve its performance.
Applications
Deep Learning has applications in various fields, such as:
- Image Recognition: Identifying objects in images and videos.
- Speech Recognition: Transcribing speech into text.
- Natural Language Processing: Understanding and generating human language.
Resources
To dive deeper into Deep Learning, check out the following resources:
- Deep Learning with Python - A comprehensive book on deep learning.
- TensorFlow - An open-source library for machine learning.
Neural Network
Image Recognition
Speech Recognition