The following notes summarize key points from the second week of the first part of Andrew Ng’s “Neural Networks and Deep Learning” course in the DeepLearning.ai project on Coursera. These notes do not cover all the details of the video lectures. For content omitted in these notes, please refer to Coursera or NetEase Cloud Classroom. … Read more
1. Introduction to Linear Regression 1.1 Origin of Regression Francis Galton, a British biologist, studied the relationship between the heights of parents and their children. He concluded that if parents are taller than the average height of the population, their children tend to be shorter than their parents, moving closer to the average height of … Read more
The BP neural network (Back Propagation) is a multi-layer network that propagates signals forward and errors backward. This network has very strong computational capabilities and can solve many nonlinear problems by analyzing the nonlinear mapping relationship between input and output variables through training samples. 1. Structure of BP Neural Network The structure of the BP … Read more
This article will coverthe essence of Gradient Descent, the principles of Gradient Descentand the algorithms of Gradient Descent in three aspects, helping you understand Gradient Descent Gradient Descent | GD. Gradient Descent 1.Essence of Gradient Descent Machine Learning’s “Three Essentials”: Select a model family, define a loss function to quantify prediction errors, and find the … Read more
Selected from severelytheoretical Translated by Machine Heart Contributors: Jiang Siyuan, Liu Xiaokun The author demonstrates through the example of deep linear networks that the reason for the poor performance of the final network is not vanishing gradients, but rather the degeneracy of the weight matrices, which reduces the effective degrees of freedom of the model, … Read more
Follow our WeChat public account “ML_NLP“ Set it as “Starred“, delivering heavy content as soon as possible! Source | https://github.com/scutan90/DeepLearning-500-questions/blob/master/ch03_%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80/%E7%AC%AC%E4%B8%89%E7%AB%A0_%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80.md Organizer | dilligencer https://zhuanlan.zhihu.com/p/105476748 This article is for interview experience sharing only and not for commercial use. If there is any infringement, please contact for deletion. 1. Why is it difficult to train deep neural … Read more
Source: Internet Introduction For almost all machine learning algorithms, whether supervised learning, unsupervised learning, or reinforcement learning, the ultimate goal generally boils down to solving optimization problems. Therefore, optimization methods play a central role in the derivation and implementation of machine learning algorithms. In this article, the author will provide a comprehensive summary of the … Read more
Introduction For almost all machine learning algorithms, whether supervised learning, unsupervised learning, or reinforcement learning, they ultimately boil down to solving optimization problems. Therefore, optimization methods play a central role in the derivation and implementation of machine learning algorithms. In this article, I will provide a comprehensive summary of the optimization algorithms used in machine … Read more
Introduction For almost all machine learning algorithms, whether supervised learning, unsupervised learning, or reinforcement learning, the final goal generally boils down to solving an optimization problem. Therefore, optimization methods occupy a central position in the derivation and implementation of machine learning algorithms. In this article, the author will provide a comprehensive summary of the optimization … Read more
Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, I felt enlightened. This article … Read more