khanhnamle1994/complete-guide-to-deep-learning
This guide is for those who know some math, know some programming language and now want to dive deep into deep learning
This guide helps aspiring machine learning practitioners understand the core concepts and techniques of deep learning. It takes you from foundational machine learning principles, through different types of neural networks like convolutional and recurrent networks, to advanced topics such as autoencoders and probabilistic graphical models. This is for individuals who possess a solid grasp of university-level mathematics and programming and are ready to delve into creating and refining deep learning models.
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Use this if you are a developer, data scientist, or researcher with a background in math and programming, eager to gain a comprehensive understanding of deep learning theory and practical implementation.
Not ideal if you are looking for a plug-and-play deep learning solution or a high-level overview without getting into the mathematical and programmatic details.
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Feb 06, 2018
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