人工智能深度学习入门视频课程.rar

[{"title":"（ 28 个子文件 970.77MB ） 人工智能深度学习入门视频课程.rar","children":[{"title":"人工智能深度学习入门视频课程","children":[{"title":"3-7 准备反向传播迭代.mp4 <span style='color:#111;'> 30.38MB </span>","children":null,"spread":false},{"title":"3-8 差异项计算.mp4 <span style='color:#111;'> 42.78MB </span>","children":null,"spread":false},{"title":"2-3 优化参数设置.mp4 <span style='color:#111;'> 30.44MB </span>","children":null,"spread":false},{"title":"3-6 损失函数定义.mp4 <span style='color:#111;'> 36.24MB </span>","children":null,"spread":false},{"title":"3-4 向量反变换.mp4 <span style='color:#111;'> 35.44MB </span>","children":null,"spread":false},{"title":"2-1 梯度下降通俗解释（以线性回归算法为例，神经网络也是如此）.mp4 <span style='color:#111;'> 24.41MB </span>","children":null,"spread":false},{"title":"2-6 神经网络架构细节.mp4 <span style='color:#111;'> 43.75MB </span>","children":null,"spread":false},{"title":"3-5 完成前向传播模块.mp4 <span style='color:#111;'> 35.15MB </span>","children":null,"spread":false},{"title":"2-4 返向传播计算方法.mp4 <span style='color:#111;'> 27.33MB </span>","children":null,"spread":false},{"title":"2-9 神经网络过拟合解决方法.mp4 <span style='color:#111;'> 36.74MB </span>","children":null,"spread":false},{"title":"1-3 计算机视觉任务.mp4 <span style='color:#111;'> 17.21MB </span>","children":null,"spread":false},{"title":"2-7 神经元个数对结果的影响.mp4 <span style='color:#111;'> 41.85MB </span>","children":null,"spread":false},{"title":"1-1 深度学习要解决的问题.mp4 <span style='color:#111;'> 21.22MB </span>","children":null,"spread":false},{"title":"3-10 完成全部迭代更新模块.mp4 <span style='color:#111;'> 58.53MB </span>","children":null,"spread":false},{"title":"1-2 深度学习应用领域.mp4 <span style='color:#111;'> 71.27MB </span>","children":null,"spread":false},{"title":"1-4 视觉任务中遇到的问题.mp4 <span style='color:#111;'> 41.10MB </span>","children":null,"spread":false},{"title":"3-9 逐层计算.mp4 <span style='color:#111;'> 38.62MB </span>","children":null,"spread":false},{"title":"3-11 手写字体识别数据集.mp4 <span style='color:#111;'> 39.55MB </span>","children":null,"spread":false},{"title":"1-5 得分函数.mp4 <span style='color:#111;'> 17.83MB </span>","children":null,"spread":false},{"title":"3-12 算法代码错误修正.mp4 <span style='color:#111;'> 53.91MB </span>","children":null,"spread":false},{"title":"2-8 正则化与激活函数.mp4 <span style='color:#111;'> 26.73MB </span>","children":null,"spread":false},{"title":"3-3 矩阵向量转换.mp4 <span style='color:#111;'> 32.17MB </span>","children":null,"spread":false},{"title":"1-7 前向传播整体流程.mp4 <span style='color:#111;'> 44.89MB </span>","children":null,"spread":false},{"title":"3-1 神经网络整体框架概述.mp4 <span style='color:#111;'> 23.26MB </span>","children":null,"spread":false},{"title":"2-2 参数更新方法.mp4 <span style='color:#111;'> 25.90MB </span>","children":null,"spread":false},{"title":"3-2 参数初始化操作.mp4 <span style='color:#111;'> 43.15MB </span>","children":null,"spread":false},{"title":"2-5 神经网络整体架构.mp4 <span style='color:#111;'> 30.12MB </span>","children":null,"spread":false},{"title":"1-6 损失函数的作用.mp4 <span style='color:#111;'> 34.90MB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]