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课程大纲
TensorFlow 基础知识
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创建、初始化、保存和恢复 TensorFlow 变量
进给、读取和预加载 TensorFlow 数据
如何使用 TensorFlow 基础结构大规模训练模型
使用 TensorBoard 可视化和评估模型
TensorFlow 力学
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输入和占位符
构建 GraphS
推理
损失
训练
从感知器到支持向量机
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内核和内核技巧
最大边距分类和支持向量
人造 Neural Networks
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非线性决策边界
前馈和反馈人工神经网络
多层感知器
最小化成本函数
前向传播
反向传播
改进神经网络的学习方式
卷积 Neural Networks
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GoALS
模型架构
原则
代码组织
启动和训练模型
评估模型
要求
物理、数学和编程背景。参与图像处理活动。
28 小时
客户评论 (5)
I liked the opportunities to ask questions and get more in depth explanations of the theory.
Sharon Ruane
课程 - Neural Networks Fundamentals using TensorFlow as Example
Very good all round overview.Good background into why Tensorflow operates as it does.
Kieran Conboy
课程 - Neural Networks Fundamentals using TensorFlow as Example
I was amazed at the standard of this class - I would say that it was university standard.
David Relihan
课程 - Neural Networks Fundamentals using TensorFlow as Example
Knowledgeable trainer
Sridhar Voorakkara
课程 - Neural Networks Fundamentals using TensorFlow as Example
I really appreciated the crystal clear answers of Chris to our questions.