In this book I hope to show you how to use the data you're already generating to make your teams, processes, and products better. The goal of the book is to teach your agile team which metrics it can use to objectively measure performance. You'll learn what data really counts, along with where to find it, how to get it, and how to analyze it. Because meaningful data may be gathered or used by any part of an agile team, you'll learn how all team members can publish their own metrics through dashboards and radiators, taking charge of communicating performance and individual accountability. Along the way, I hope you'll pick up practical data analysis techniques, including a few emerging Big Data practices.

[IT服务管理指标].(Metrics.for.IT.Service.Management).Peter.Brook.扫描版

kubernetes性能监控工具metrics-server离线镜像， k8s.gcr.io/metrics-server-amd64:v0.3.6 ，使用方法：docker load -i metrics-server.tar

波士顿房价 这是 sklearn.datasets 里的一种 Toy Dataset ，包含503个美国波士顿房价的观测值，是内置的小数据集，也是研究回归算法的优秀数据集。 Python编程实现 import matplotlib.pyplot as plt import matplotlib.font_manager as fm import numpy as np import pandas as pd from sklearn.datasets import load_boston from sklearn.model_selection import train_test_split

此命令行程序将计算从1（二十面体）到100或更高的任何频率的测地球（或球顶）。 目前仅支持I类频率计算。 可以输出详细的PostScript图和数据。

Mastering ’Metrics The Path from Cause to Effect

P. Turri的airopa_benchmarks的修改版本。

k8s.gcr.io/kubernetes-metrics-scraper:v1.0.1镜像tar包，使用 docker load --input kubernetes-metrics-scraper_v1.0.1.tar进行导入

修复了hystrix-metrics-event-stream-1.5.18.jar版本的/acutor/hystrix.stream的bug。 对应博客https://blog.csdn.net/liufang1991/article/details/114970154

在keras的loss库中添加rmse方法，成功使模型能正常使用rmse方法。在metrics.py文件上添加rmse方法后可以使用model.compile(loss='mse'，weighted_metrics=['rmse'])方法，可以在其他loss的条件下观测rmse的变化