This tutorial will give an introduction into neural networks and the basics of deep learning. After a short review of basic machine learning techniques (supervised learning, classification, lossfunction and optimizers), the mathematical background of neural networks will be covered, including multilayer perceptrons, gradient descent and backpropagation. These concepts will be introduced in the context of logistic regression, which itself comprises a well known machine learning modell. Practical application of neural networks will be illustrated on the well known example of hand-written number recognition
This textbook presents a concise, accessible and engaging first introduction to deep learning, offer...
The basic structure and definitions of artificial neural networks are exposed, as an introduction to...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
The purpose of this chapter is to introduce a powerful class of mathematical models: the artificial ...
Developments in deep learning with ANNs (Artificial Neural Networks) are paving the way for revoluti...
This book covers both classical and modern models in deep learning. The primary focus is on the theo...
In this half-day tutorial, participants first explore the fundamentals of feed-forward neural networ...
This is Chapter 3 of the book titled "Deep Learning": a nine-part easy-to-grasp textbook written wit...
Deep learning is a technique of machine learning in artificial intelligence area. Deep learning in a...
An overview of neural networks, covering multilayer perceptrons, radial basis functions, constructiv...
In the past few years, Deep Learning has generated much excitement in Machine Learning and industry ...
This is Chapter 1 of Part 1 of the book titled "Deep Learning": a nine-part easy-to-grasp textbook w...
In this chapter the authors present the theory and mathematics behind artificial neural networks (AN...
Neural networks are computing systems modelled after the biological neural network of animal brain a...
Treballs finals del Màster en Matemàtica Avançada, Facultat de matemàtiques, Universitat de Barcelon...
This textbook presents a concise, accessible and engaging first introduction to deep learning, offer...
The basic structure and definitions of artificial neural networks are exposed, as an introduction to...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
The purpose of this chapter is to introduce a powerful class of mathematical models: the artificial ...
Developments in deep learning with ANNs (Artificial Neural Networks) are paving the way for revoluti...
This book covers both classical and modern models in deep learning. The primary focus is on the theo...
In this half-day tutorial, participants first explore the fundamentals of feed-forward neural networ...
This is Chapter 3 of the book titled "Deep Learning": a nine-part easy-to-grasp textbook written wit...
Deep learning is a technique of machine learning in artificial intelligence area. Deep learning in a...
An overview of neural networks, covering multilayer perceptrons, radial basis functions, constructiv...
In the past few years, Deep Learning has generated much excitement in Machine Learning and industry ...
This is Chapter 1 of Part 1 of the book titled "Deep Learning": a nine-part easy-to-grasp textbook w...
In this chapter the authors present the theory and mathematics behind artificial neural networks (AN...
Neural networks are computing systems modelled after the biological neural network of animal brain a...
Treballs finals del Màster en Matemàtica Avançada, Facultat de matemàtiques, Universitat de Barcelon...
This textbook presents a concise, accessible and engaging first introduction to deep learning, offer...
The basic structure and definitions of artificial neural networks are exposed, as an introduction to...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...