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所在平台: Udemy |
课程主页: https://www.udemy.com/course/neural-network-in-csharp-from-scratch/
课程评论：没有评论
课程名称：从零开始的C#神经网络 课程概述：在这门课程中，我们将深入探讨神经网络、机器学习和变压器的基本概念。即使您已经了解了一些相关知识，或者尝试过应用这些概念，但可能仍然觉得缺乏对核心内容的理解。为了填补这一空缺，我设计了这门实践性课程，我们将共同学习神经网络的主要特征，包括：层、神经元、连接、前向传播、反向传播以及损失的可视化。 课程中特别强调反向传播的过程，通过逐步讲解偏导数的计算，帮助您深入理解这一过程。我们将使用专为本课程创建的深度神经网络图示，图形化的方法将使得我们所编码的内容更为直观，逐个模型进行分析。 一旦我们构建完成神经网络，我们还将对更复杂的函数进行测试，以观察如何改进预测结果。课程中将使用面向对象的建模和一些函数式编程的技巧。 如果您对以实践编码方式理解神经网络感兴趣，欢迎加入这门课程。
I am sure you heard about neural networks, machine learning and transformers. Maybe you are already familiar with some of the concepts surrounding these fields, or even tried a practical approach already, but still feel you are missing something.I know I have felt this way even after taking several courses and learning special libraries(python I am looking at you). I always felt I somehow missed the point. That is why I created this hands on course, where together we go over main features of Neural Networks including:LayersNeuronsConnectionsFeed ForwardBackpropagationVisualizing the LossWe will use our own deep neural network diagram, created specifically for this course. Using such graphical approach will make it easier to understand what we are coding, model by model.Specific emphasis is put on backpropagation, where I guide you through an article with step by step explanations of partial derivatives calculation for our diagram.Once we build our neural network we also test it on more demanding functions and see how we can improve predictions.We use object oriented modelling and a bit of functional programming along the way.So, if you are interested in a practical coding approach to understanding neural networks, join me in this course.
