An Introduction to Deep Learning

Deep learning is an exciting new field of machine learning that has been gaining popularity recently

Deep learning is a type of artificial intelligence (AI) that uses multiple layers of neural networks to learn tasks. It was first developed in the 1980s by researchers at IBM and Stanford University.


What Is Deep Learning? (What Is Machine Learning?)


Deep learning is a type of artificial intelligence that uses multiple layers of neural networks to learn patterns in data. It was first introduced in the 1980s, but only recently has it become more popular due to advances in computing power.


Why Do You Need Deep Learning?


Deep learning is used in areas such as speech recognition, computer vision, natural language processing, and robotics. These applications use deep learning to analyze large amounts of data and make predictions based on those analyses.


Practical Examples of Using Deep Learning


There are two main ways to use deep learning: supervised learning and unsupervised learning. Supervised learning requires training data with labels. Unsupervised learning does not require labeled data.


Some practical examples of using deep learning in Python.


Deep learning is a form of AI that involves creating algorithms with multiple layers of neural networks. These networks are inspired by the human brain's ability to process data. They're used to perform complex tasks such as speech recognition, image classification, and natural language processing.


The Basics of Neural Networks


A neural network is a type of artificial intelligence (AI) system that mimics the human brain by using layers of interconnected nodes to perform tasks. It's also called a "neural net" because its structure resembles the arrangement of neurons in the human brain.

Keyvan Kasaei

A Business & Technology Leader, Keyvan drives the Strategy and Sales at Padiso