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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    DeepLearning.AI

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    Copenhagen Business School

    Skills you'll gain: Artificial Intelligence, Large Language Modeling, Natural Language Processing, Theoretical Computer Science, Statistical Machine Learning, Statistical Analysis, Artificial Neural Networks, Responsible AI, Computational Thinking, Human Computer Interaction

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    Dartmouth College

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    Università di Napoli Federico II

    Skills you'll gain: PyTorch (Machine Learning Library), NumPy, Image Analysis, Pandas (Python Package), Matplotlib, Artificial Neural Networks, Deep Learning, Computer Vision, Keras (Neural Network Library), Jupyter, Data Manipulation, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Python Programming, Data Science, Scikit Learn (Machine Learning Library)

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