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EITCA Academy

The European Information Technologies Certification Institute - EITCI ASBL

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EITCI Institute ASBL

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Questions and answers designated by tag: Backpropagation

Does PyTorch directly implement backpropagation of loss?

Friday, 14 June 2024 by dkarayiannakis

PyTorch is a widely used open-source machine learning library that provides a flexible and efficient platform for developing deep learning models. One of the most significant aspects of PyTorch is its dynamic computation graph, which enables efficient and intuitive implementation of complex neural network architectures. A common misconception is that PyTorch does not directly handle

  • Published in Artificial Intelligence, EITC/AI/DLPP Deep Learning with Python and PyTorch, Introduction, Introduction to deep learning with Python and Pytorch
Tagged under: Artificial Intelligence, Autograd, Backpropagation, Gradient Descent, Neural Networks, PyTorch

What are the historical models that laid the groundwork for modern neural networks, and how have they evolved over time?

Tuesday, 21 May 2024 by EITCA Academy

The development of modern neural networks has a rich history, rooted in early theoretical models and evolving through several significant milestones. These historical models laid the groundwork for the sophisticated architectures and algorithms we use today in deep learning. Understanding this evolution is important for appreciating the capabilities and limitations of current neural network models.

  • Published in Artificial Intelligence, EITC/AI/ADL Advanced Deep Learning, Neural networks, Neural networks foundations, Examination review
Tagged under: Artificial Intelligence, Backpropagation, CNN, DBN, GAN, Hebbian Learning, LSTM, McCulloch-Pitts, Perceptron, RNN, Transformer

What is a neural network?

Wednesday, 10 January 2024 by Daniel Forment

A neural network is a computational model inspired by the structure and functioning of the human brain. It is a fundamental component of artificial intelligence, specifically in the field of machine learning. Neural networks are designed to process and interpret complex patterns and relationships in data, allowing them to make predictions, recognize patterns, and solve

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Further steps in Machine Learning, Big data for training models in the cloud
Tagged under: Activation Function, Artificial Intelligence, Artificial Neurons, Backpropagation, Feedforward Neural Network, Neural Networks

What is the vanishing gradient problem?

Monday, 14 August 2023 by Brian Buckley

The vanishing gradient problem is a challenge that arises in the training of deep neural networks, specifically in the context of gradient-based optimization algorithms. It refers to the issue of exponentially diminishing gradients as they propagate backwards through the layers of a deep network during the learning process. This phenomenon can significantly hinder the convergence

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, First steps in Machine Learning, Deep neural networks and estimators
Tagged under: Activation Functions, Artificial Intelligence, Backpropagation, Deep Learning, Gradient Descent, Vanishing Gradient Problem

How is the loss calculated during the training process?

Sunday, 13 August 2023 by EITCA Academy

During the training process of a neural network in the field of deep learning, the loss is a important metric that quantifies the discrepancy between the predicted output of the model and the actual target value. It serves as a measure of how well the network is learning to approximate the desired function. To understand

  • Published in Artificial Intelligence, EITC/AI/DLPP Deep Learning with Python and PyTorch, Neural network, Training model, Examination review
Tagged under: Artificial Intelligence, Backpropagation, Deep Learning, Loss Function, Machine Learning, Neural Networks

What is the purpose of backpropagation in training CNNs?

Sunday, 13 August 2023 by EITCA Academy

Backpropagation serves a important role in training Convolutional Neural Networks (CNNs) by enabling the network to learn and update its parameters based on the error it produces during the forward pass. The purpose of backpropagation is to efficiently compute the gradients of the network's parameters with respect to a given loss function, allowing for the

  • Published in Artificial Intelligence, EITC/AI/DLPTFK Deep Learning with Python, TensorFlow and Keras, Convolutional neural networks (CNN), Introduction to convolutional neural networks (CNN), Examination review
Tagged under: Artificial Intelligence, Backpropagation, Convolutional Neural Networks, Deep Learning, Gradient Descent, Optimization

What is the role of the optimizer in TensorFlow when running a neural network?

Tuesday, 08 August 2023 by EITCA Academy

The optimizer plays a important role in the training process of a neural network in TensorFlow. It is responsible for adjusting the parameters of the network in order to minimize the difference between the predicted output and the actual output of the network. In other words, the optimizer aims to optimize the performance of the

  • Published in Artificial Intelligence, EITC/AI/DLTF Deep Learning with TensorFlow, TensorFlow, Running the network, Examination review
Tagged under: Artificial Intelligence, Backpropagation, Deep Learning, Neural Network, Optimizer, TensorFlow

What is backpropagation and how does it contribute to the learning process?

Tuesday, 08 August 2023 by EITCA Academy

Backpropagation is a fundamental algorithm in the field of artificial intelligence, specifically in the domain of deep learning with neural networks. It plays a important role in the learning process by enabling the network to adjust its weights and biases based on the error between the predicted output and the actual output. This error is

  • Published in Artificial Intelligence, EITC/AI/DLTF Deep Learning with TensorFlow, Introduction, Introduction to deep learning with neural networks and TensorFlow, Examination review
Tagged under: Artificial Intelligence, Backpropagation, Deep Learning, Neural Networks, TensorFlow

How does a neural network learn during the training process?

Tuesday, 08 August 2023 by EITCA Academy

During the training process, a neural network learns by adjusting the weights and biases of its individual neurons in order to minimize the difference between its predicted outputs and the desired outputs. This adjustment is achieved through an iterative optimization algorithm called backpropagation, which is the cornerstone of training neural networks. To understand how a

  • Published in Artificial Intelligence, EITC/AI/DLTF Deep Learning with TensorFlow, Introduction, Introduction to deep learning with neural networks and TensorFlow, Examination review
Tagged under: Artificial Intelligence, Backpropagation, Deep Learning, Neural Networks, Optimization, Training Process

What are neural networks and how do they work?

Tuesday, 08 August 2023 by EITCA Academy

Neural networks are a fundamental concept in the field of artificial intelligence and deep learning. They are computational models inspired by the structure and functioning of the human brain. These models consist of interconnected nodes, or artificial neurons, which process and transmit information. At the core of a neural network are layers of neurons. The

  • Published in Artificial Intelligence, EITC/AI/DLTF Deep Learning with TensorFlow, Introduction, Introduction to deep learning with neural networks and TensorFlow, Examination review
Tagged under: Artificial Intelligence, Backpropagation, Deep Learning, Neural Networks, TensorFlow
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The European IT Certification framework has been established in 2008 as a Europe based and vendor independent standard in widely accessible online certification of digital skills and competencies in many areas of professional digital specializations. The EITC framework is governed by the European IT Certification Institute (EITCI), a non-profit certification authority supporting information society growth and bridging the digital skills gap in the EU.

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