% TODO: Compute the linear regression objective by looping over the examples in X. % Store the objective function value in 'f'. % % TODO: Compute the gradient of the objective with respect to theta by looping over % the examples in X and adding up the gradient for each example. Store ...
deeplearning.ai 笔记 Specialization 1 week 2 Python and Vectorization broadcasting in Python:b是一个实数,但是和矩阵相加的时候会自动扩展为一个行向量。 红圈(下面的两个)即实现m个样本的正向传播。 Vectorizing Logistic Regression's Gradient Output 向量化逻辑回归的实现: 将逻辑回归向量化的过程,将两个for...
% TODO: Compute the linear regression objective by looping over the examples in X. % Store the objective function value in 'f'. % % TODO: Compute the gradient of the objective with respect to theta by looping over % the examples in X and adding up the gradient for each example. Store ...
You might be wondering why we’ve taken a detour off into the land of vectorization in a book about deep learning. The main reason is that most machine learning books focus purely on the algorithms themselves and less so on the complete lifecycle of data mining. We want to experiment with...
更改train.m的参数设置 visibleSize =28*28; %number of input units hiddenSize=196; %number of hidden units sparsityParam=0.1; %desired average activation of the hidden units.% (This was denoted by the Greek alphabet rho, which looks like a lower-case"p",%inthe lecture notes). ...
deeplearning.ai 笔记 Specialization 1 week 2 Python and Vectorization Regression's Gradient Output 向量化逻辑回归的实现:将逻辑回归向量化的过程,将两个for循环都去掉了,虽然说尽量去掉for循环有利于代码的执行速度,但是迭代次数的for循环是去不掉...表示计算竖直方向(也就是一列)的值,对应axis=1 代表的是水...
thorough experimentation and optimization, which is a significant improvement compared to previous studies' highest accuracy of 96%. We demonstrate our method's unmatched accuracy in identifying fake news reports by utilizing deep learning and the comprehensive features of the Truth Seeker 2023 dataset....
01. What is Deep Learning02. What is a Neural Network03. Supervised Learning with Neural Networks04. Drivers Behind the Rise of Deep Learning05. Binary Classification in Deep Learning06. Logistic Regression07. Logistic Regression Cost Function08. Gradient Descent09. Derivatives10. Derivatives Examples...
Every Bit Counts: Using Deep Learning and Vectorization to Analyze Healthcare Big DataThe rapid digitization of healthcare has generated large volumes of rich and complex data from sources such as claims and electronic health records. Traditional...
2 还有从旧教程http://deeplearning.stanford.edu/wiki/index.php/Exercise:Softmax_Regression 学了 % M is the matrix as described in the text M = bsxfun(@rdivide, M, sum(M)) 3 新教程学到了 I=sub2ind(size(A),1:size(A,1), y);values= A(I); ...