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类神经网路的原理介绍以及其在 Wolfram 语言里的使用

我们会介绍深度学习中的类神经网路的基本原理,包括基本结构、激励函数(activation function)、优化算法的概念以及梯度下降法、批归一化、池化层,还有其他重要的技术和原理。并且会介绍对应的组件在 Wolfram 语言中的使用方法以及应用。

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701 videos match your search.
Mads (Mohammad) Bahrami
Mads (Mohammad) Bahrami
In this video, we review concepts of quantum basis and quantum state (in a finite-dimensional Hilbert space) and how to implement them in the Wolfram Quantum Framework. We also discuss the basis transformation. For more info and examples, please visit ...
Mads (Mohammad) Bahrami
In this video, we review the quantum measurement operator and quantum measurement in the Wolfram Quantum Framework. We discuss the implementation of both projective measurements and also POVMs. For more ...
Mads (Mohammad) Bahrami
In this video, we show how one can construct a quantum circuit using the Wolfram Quantum Framework. We discuss the implementation of some examples such as quantum teleportation. For more ...
Mads (Mohammad) Bahrami
In this video, we review our multi-part discussion of the Wolfram Quantum Framework and discuss how it works, how to define relevant objects (such as a quantum circuit) and how ...
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