https://www.youtube.com/watch?v=Ilg3gGewQ5U&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi&index=3&pp=iAQB 知识 科学科普 人工智能 cniclsh 发消息 接下来播放 自动连播 Attention in transformers, visually explained Chapter 6, Deep Learning cniclsh 0 0 How might LLMs store facts Chapter 7, ...
What Does Backpropagation Mean? Backpropagation is an algorithm used in artificial intelligence (AI) to fine-tune mathematical weight functions and improve the accuracy of anartificial neural network’soutputs. Advertisements A neural network can be thought of as a group of connected input/output (I...
训练还需要让它接触预处理数据集,并反复更新其参数,以最小化预测模型输出与实际输出之间的差异。这一过程被称为反向传播(backpropagation),可以让模型了解数据中的潜在模式和关系。 在初始训练后,针对特定任务或领域对大型语言模型进行微调,可进一步提高其性能。对 LLM 进行微调可使其适应特定环境并实现专业化,从而使...
Backpropagation is a training algorithm used for a multilayer neural networks, it allows for efficient computation of the gradient. The backpropagation algorithm can be divided into several steps: 1) Forward propagation of training data through the network in order to generate output. 2) Use target...
By thinking of our network as a tree of these elementary operations, we can now do a lot of things very easily with recursion, which will form the basis of both our backpropagation and forward propagation algorithms. In code, we can define a recursive neural network class that looks like ...
The key difference here is that static backpropagation offers instant mapping, while recurrent backpropagation does not.Advantages and disadvantages of backpropagation algorithms There are several advantages to using a backpropagation algorithm, but it also comes with challenges. Advantages of backpropagatio...
摘要: Basic backpropagation, which is a simple method now being widely used in areas like pattern recognition and fault diagnosis, is reviewed. The basic equations for backpropagation through time, and applications to areas like pattern recognition involvi......
Watching this video of Blake Richard, at about 11 minutes, he says that he have been thinking for a long time on how the brain could do backpropagation or something similar to it. And he says that in Deep Learning, we have stripped the complexity out of the neurons and that r...
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Auto-differentiation: PyTorch model allows developers to easily calculate gradients and perform backpropagation with its automatic differentiation capabilities. High Performance: PyTorch is equipped with an optimized C++ backend, making it highly performant. Distributed Computing: PyTorch supports distributed com...