为了解决官网下载OpenCV比较慢，所以上传了这个资源包 这个资源包里包含了 opencv-4.8.0-windows.exe : windows下的包 opencv-4.8.0-android-sdk.zip : Android下的包 opencv-4.8.0.zip : openCV的源码 具体openCV的使用，可以看我的博客 : https://blog.csdn.net/EthanCo/article/details/131911635

这是Python3.5版本的win32com。下载后用命令pip install *.whl即可安装。

这个软件个人使用感觉一般，但是因为科学上网等原因，还是分享一下吧。 整体使用下来，有时候会比较卡顿，但是由于你可以随时随地的浏览自己收藏的论文，然后批注啥的也是同步的，所以对于文献阅读还是有帮助的。 有各种插件，可以自行探索，然后就是这个软件是有网页版的，可以去看看。大概就是这些，为了提高曝光，随便水一些字好了： 上方菜单栏-》help-》create backup 这个好像不错，得到的是一个zip。里面包含一个database.sqlite文件。 在电脑1 create backup 将电脑1中的pdf文件存储文件夹copy到电脑2中，注意：路径要相同。 将电脑1的backup复制到电脑2，然后在电脑2的mendeley中restore backup。

xptable控件下载 (源代码和演示)，包括源代码和演示，详细介绍了每一个用法和代码，值的学习和使用。

找了好久才找到，适用于芯片型号为：AU6998AN/AU6989AN/SC908AN的u盘量产，由于本人u盘不知道怎么有了写保护，试尽各种方法无果，量产工具也找了一大堆，无一成功，今天突然发现这款，一气呵成，欣喜若狂，遂无偿分享之，希望能为具有相同遭遇的朋友解决困惑。

Python Machine Learning By Example by Yuxi (Hayden) Liu English | 31 May 2017 | ASIN: B01MT7ATL5 | 254 Pages | AZW3 | 3.86 MB Key Features Learn the fundamentals of machine learning and build your own intelligent applications Master the art of building your own machine learning systems with this example-based practical guide Work with important classification and regression algorithms and other machine learning techniques Book Description Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. What you will learn Exploit the power of Python to handle data extraction, manipulation, and exploration techniques Use Python to visualize data spread across multiple dimensions and extract useful features Dive deep into the world of analytics to predict situations correctly Implement machine learning classification and regression algorithms from scratch in Python Be amazed to see the algorithms in action Evaluate the performance of a machine learning model and optimize it Solve interesting real-world problems using machine learning and Python as the journey unfolds About the Author Yuxi (Hayden) Liu is currently a data scientist working on messaging app optimization at a multinational online media corporation in Toronto, Canada. He is focusing on social graph mining, social personalization, user demographics and interests prediction, spam detection, and recommendation systems. He has worked for a few years as a data scientist at several programmatic advertising companies, where he applied his machine learning expertise in ad optimization, click-through rate and conversion rate prediction, and click fraud detection. Yuxi earned his degree from the University of Toronto, and published five IEEE transactions and conference papers during his master's research. He finds it enjoyable to crawl data from websites and derive valuable insights. He is also an investment enthusiast. Table of Contents Getting Started with Python and Machine Learning Exploring the 20 newsgroups data set Spam email detection with Naive Bayes News topic classification with Support Vector Machine Click-through prediction with tree-based algorithms Click-through rate prediction with logistic regression Stock prices prediction with regression algorithms Best practices

为您提供纯真ip数据库下载，纯真QQ IP数据库收集包括中国电信、中国网通、长城宽带、网通宽带、聚友宽带等 ISP 的最新准确IP地址数据，五天更新一次。基本简介　　纯真ip数据库是一款简单实用的IP地址查看工具，通过该软件，你可以输入IP查看地址、也可以输入地址查看IP，　　还能根据自己掌握的信息查询任意IP段，可以显示全国范围内和您在同一内部网的IP信息非常方便；　　纯真ip数据库操作简单，使用方便，您可以辅助数据地址，

小票打印机教程

各种算法来通过 Matlab 解决 LASSO 问题，包括： 投影梯度法，通过将原始问题重新表述为具有框约束的二次规划 原始问题的次梯度方法 平滑原始问题的梯度方法 平滑原始问题的快速梯度法 原始问题的近似梯度法 原始问题的快速近端梯度法 对偶问题的增强拉格朗日方法 对偶问题的乘法器交替方向法 原问题线性化乘法器的交替方向法 AdaGrad、Adam、RMSProp、使用次梯度的动量

透明图标下载