인공지능 썸네일형 리스트형 Neural Networks and Deep Learning (3) Neural Networks BasicsLogistic Regression as a Neural NetworkComputation GraphA computation graph is an organized forward pass (propagation) to compute the function of a neural network, followed by a backward pass (propagation) to calculate the gradients of a neural network.This is like looking at a math formula and calculating step by step to get the answer. One step of ________ propagation on .. 더보기 Neural Networks and Deep Learning (2) Neural Networks BasicsSet up a machine learning problem with a neural network mindset and use vectorization to speed up your models.Learning ObjectivesBuild a logistic regression model structured as a shallow neural networkBuild the general architecture of a learning algorithm, including parameter initialization, cost function, gradient calculation, and optimization implementation (gradient desc.. 더보기 Neural Networks and Deep Learning (1) Introduction to Deep LearningQuizQ1What does the analogy “AI is the new electricity” refer to?AI is powering personal devices in our homes and offices, similar to electricity.Like electricity started about 100 years ago, AI is transforming multiple industries.Through the “smart grid”, AI is delivering a new wave of electricity.AI runs on computers and is thus powered by electricity, but it is le.. 더보기 Neural Networks and Deep Learning (0) About this CourseIn the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning.By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters i.. 더보기 이전 1 2 3 다음
