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"

  • Status: Free Trial

    Whizlabs

    Skills you'll gain: Deep Learning, Image Analysis, Computer Vision, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Tensorflow, Applied Machine Learning, Machine Learning, Supervised Learning, Machine Learning Algorithms, Data Processing, Linear Algebra, Network Architecture

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    Rating, 4.4 out of 5 stars
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    Packt

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    Intermediate · Course · 1 - 4 Weeks

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    Packt

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    Beginner · Course · 3 - 6 Months

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    Packt

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  • Status: Preview

    Arm

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    4.4
    Rating, 4.4 out of 5 stars
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    Advanced · Course · 1 - 3 Months

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    Packt

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    DeepLearning.AI

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    Rating, 4.7 out of 5 stars
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    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview

    Universidade de São Paulo

    Skills you'll gain: Natural Language Processing, Artificial Neural Networks, Tensorflow, Python Programming, Applied Machine Learning, Deep Learning, Artificial Intelligence, Text Mining, Data Processing

    4.6
    Rating, 4.6 out of 5 stars
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    Intermediate · Course · 1 - 3 Months

  • Status: New
    Status: Free Trial

    Simplilearn

    Skills you'll gain: Generative AI, Generative Model Architectures, Deep Learning, Tensorflow, Applied Machine Learning, Artificial Neural Networks, Unsupervised Learning, Image Quality

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