How can I learn artificial neural network?
Answers from top 10 papers
|An artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving complex problems.|
01 Jan 2005
|Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems.|
01 Jan 2015
|Artificial Neural Network (ANN)s are trained by back propagating the error derivatives and therefore have the potential to learn much better models of nonlinear data.|
01 Oct 1999-Process Biochemistry
|The artificial neural network technique is powerful because it can learn to represent complicated data patterns or data relationships between input and output variables of the system being studied.|
01 Jan 2004-Neuroinformatics
|When exposed to complex data sets, artificial neural networks (ANNs) can recognize patterns, learn the relationship of different variables, and address classification tasks.|
31 Dec 2016-Research on computing science
|Artificial Neural Networks have proven to be a very powerful machine learning algorithm which can be adequate to learn successfully a variety of tasks.|
|Neural network systems can be made to learn faster and generalize better through the addition of knowledge.|
|By adapting the interconnections between layers, Artificial Neural networks are able to learn.|
01 Aug 2002-Neurocomputing
|It is shown that modifying the sigmoidal basis function of a multi-layer feedforward artificial neural network using a control parameter improves the network's ability to learn.|
01 May 2011-Computers & Electrical Engineering
|By using these tools, users can also understand and learn working mechanism of a typical artificial neural network, using features of different models and related learning algorithms.|
How can I learn deep learning?3 answersTo learn deep learning, it is important to become familiarized with the basic concepts and principles. Deep learning involves creating high level abstractions from data using large neural networks. It encompasses new concepts and methods beyond just neural networks. Start by revising some works relating to physics and deep learning. Then, learn about the main elements, their use, and several possible network architectures. Familiarity with linear algebra, multivariate calculus, and probability and statistics is required. Additionally, gaining practical experience by working through programs in machine learning frameworks like Tensorflow is beneficial. Deep Learning by Goodfellow, Bengio, and Courville is a comprehensive resource that covers mathematical and conceptual background, deep learning techniques, and applications. The Science of Deep Learning by Tang is another resource that covers the foundations of deep learning and key architectures.
How artificial neural network works in machine learning?10 answers
How to create an artificial neural network?10 answers
What is learning in artificial neural network?10 answers
What is training in artificial neural network?10 answers
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