吴恩达《神经网络和深度学习》课程总结

本文是作者学习吴恩达的深度学习专项课程《神经网络和深度学习》后的个人总结,涵盖了从深度学习简介、逻辑回归作为神经网络、浅层神经网络到深层神经网络的要点,包括监督学习、激活函数、反向传播等概念,并附有编程作业概述。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

本文新地址:此处

Note

This is my personal summary after studying the course neural-networks-deep-learning, which belongs to Deep Learning Specialization. and the copyright belongs to deeplearning.ai.

My personal notes

1st weekintroduction-to-deep-learning

2nd week: neural-networks-basics

3rd weekshallow-neural-networks

4th weekdeep-neural-networks

My personal programming assignments

week 1 and week 2: logistic-regression-with-a-neural-network-mindset
week 3: Planar data classification with a hidden layer
week 4 part 1: Building your deep neural network: Step by Step
week 4 part 2: deep-neural-network-application

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值