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Oreilly - Data Science and Machine Learning Series: Deep Learning: Facts, Frameworks, and Functionality
Categories: Tutorials
Oreilly - Data Science and Machine Learning Series: Deep Learning: Facts, Frameworks, and Functionality - 9781634623483
Oreilly - Data Science and Machine Learning Series: Deep Learning: Facts, Frameworks, and Functionality
by Zacharias Voulgaris | Released February 2018 | ISBN: None


Explore deep learning and how it applies to data science and compares to traditional machine learning. See how deep learning works in terms of both architecture and design, and learn about different frameworks including Apache MXNet, PyTorch, and TensorFlow. Related concepts are covered including Artificial Neural Networks (ANNs), Multi-Layer Perceptrons (MLPs), and Natural Language Processing (NLP). Programming languages including Python and Julia are discussed.Here is a link to all of Zacharias Voulgaris' machine learning, data science, and artificial intelligence (AI) videos. Show and hide more
  1. Deep Learning: Facts, Frameworks, and Functionality 00:28:04
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    Oreilly - Data Science and Machine Learning Series: Deep Learning: Facts, Frameworks, and Functionality


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