吴恩达《深度学习》-第一门课 (Neural Networks and Deep Learning)-第二周:(Basics of Neural Network programming)-课程笔记 第二周:神经网络的编程基础 (Basics of Neural Network programming) 2.1、二分类(Binary Classification) 二分类问题的目标就是习得一个分类器,它以图片的特征向量(RGB值的矩阵,最后延展...
Neural networks are one of the most important models in machine learning. The structure of artificial neural networks, which consists of numerous neurons with connections to each other, bears great resemblance to that of biological neural networks. A neural network learns in the following way: ...
第二周:神经网络的编程基础(Basics of Neural Network programming) 二分类(Binary Classification) 这周我们将学习神经网络的基础知识,其中需要注意的是,当实现一个神经网络的时候,我们需要知道一些非常重要的技术和技巧。例如有一个包含mm个样本的训练集,你很可能习惯于用一个 for 循环来遍历训练集中的每个样本,但是...
【吴恩达深度学习专栏】神经网络的编程基础(Basics of Neural Network programming)——导数(Derivatives)、更多的导数例子(More Derivative,程序员大本营,技术文章内容聚合第一站。
本节课主要介绍了衡量Neural Networks的效率指标,旨在模型更小,计算更快,耗能更少。主要指标包括,衡量memory的参数量,model size, #Activations,以及衡量计算量的MACs, FLOP(s), OP(s). 这些都在本节课的偏后部分,前面复习了各种网络结构,以CV/AlexNet为主,后面的计算用了AlexNet的例子来计算各种指标。
slope of function Computation Graph Vectorization 用python的np.dot运行比for loop速度快300多倍 (当纬度为10000) Vetorizing Logistic Regression Pythonnumpy的传播性 Broadcasting in Python 在numpy中.sum()函数 默认参数为axis=none .sum(axis=none) 把矩阵所有值相加 .sum(axis=0)把矩阵按行相加 .sum(axis...
Note: You should choose values so that the number of nodes does not exceed the number of continuous predictors plus the total number of categories across all categorical (flag, nominal, and ordinal) predictors. Parent topic: Neural networks ...
COURSE 1 Neural Networks and Deep Learning Week1 What is neural network? It is a powerful learning algorithm inspired by how the brain works. Example 1 - single neural network Given data about the size of houses on the real estate market and y......
EfficientML.ai Lecture 2 - Basics of Neural Networks (MIT 6.5940, Fall 2023, Zoom recording)Lecture 2 - Basics of Neural NetworksInstructor: Prof. Song HanSlides: https://efficientml.ai, 视频播放量 1107、弹幕量 2、点赞数 15、投硬币枚数 4、收藏人数 12、转
Connecting multiple neural networks together, altering the directionality of their weights and stacking such machines all gave rise to the increasing power and popularity of DL. 通常你可能会看到CNN和DL的混淆,但DL的概念是在CNN首次被引入之前的一段时间提出的。将多个神经网络连接在一起,改变其权重的方向...