摘要: 本文是吴恩达 (Andrew Ng)老师<机器学习>课程,第一章<绪论:初识机器学习>中第4课时<无监督学习>的视频原文字幕.为本人在视频学习过程中逐字逐句记录下来以便日后查阅使用.现分享给大家.如有错误,欢迎大家批评指正,在此表示诚挚地感谢!同时希望对大家的学习能有所帮助. In this video (article), we'll talk about the second major type of machine learning problem, c…
1 Unsupervised Learning 1.1 k-means clustering algorithm 1.1.1 算法思想 1.1.2 k-means的不足之处 1.1.3 如何选择K值 1.1.4 Spark MLlib 实现 k-means 算法 1.2 Mixture of Gaussians and the EM algorithm 1.3 The EM Algorithm 1.4 Principal Components…
Unsupervised Learning: Use Cases Contents Visualization K-Means Clustering Transfer Learning K-Nearest Neighbors The features learned by deep neural networks can be used for the purposes of classification, clustering and regression. Neural nets are s…
Unsupervised learning refers to data science approaches that involve learning without a prior knowledge about the classification of sample data. In Wikipedia, unsupervised learning has been described as "the task of inferring a function to describe h…
Supervised Learning In supervised learning, we are given a data set and already know what our correct output should look like, having the idea that there is a relationship between the input and the output. Supervised learning problems are categorized…
Unsupervised learning allows us to approach problems with little or no idea what our results should look like. We can derive structure from data where we don't necessarily know the effect of the variables. We can derive this structure by clustering t…
PredNet --- Deep Predictive coding networks for video prediction and unsupervised learning ICLR 2017 2017.03.12 Code and video examples can be found at: https://coxlab.github.io/prednet/ 摘要:基于监督训练的深度学习技术取得了非常大的成功,但是无监督问题仍然是一个未能解决的一大难题(从未标注的数据中学习到…
Introduction to Learning to Trade with Reinforcement Learning http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/ Thanks a lot to @aerinykim, @suzatweet and @hardmaru for the useful feedback! The academic Deep…
@(131 - Machine Learning | 机器学习) 零. Goal How Unsupervised Learning fills in that model gap from the original Machine Learning work flow 2.How to compare different models developed using Unsupervised Learning for their relative strengths and relative…