Artificial Neural Networks

Artificial Neural Networks (ANN) are computing systems inspired by biological neural networks that are the backbone of artificial intelligence (AI) and machine learning. Coursera's ANN skill catalogue teaches you the fundamentals and applications of these complex systems. You'll learn about the architecture of ANN, including layers, nodes, activation functions, and backpropagation. You'll understand how to train ANN for tasks such as pattern recognition, prediction, and decision making. Further, you will explore various types of neural networks like Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Deep Neural Networks (DNN). This knowledge will equip you to develop cutting-edge AI applications in various fields such as computer vision, natural language processing, and robotics.
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Results for "artificial neural networks"

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    University of Colorado Boulder

    Skills you'll gain: Data Mining, Unsupervised Learning, Big Data, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Data Analysis, Anomaly Detection, Machine Learning Algorithms, Advanced Analytics, Statistical Analysis, Predictive Modeling, Network Analysis, Exploratory Data Analysis, Bayesian Statistics, Algorithms, Artificial Neural Networks, Scalability

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    Dartmouth College

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    Università di Napoli Federico II

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