Ronalchan的博客

黑苹果的EFI文件，替换引导，无忧下载，助力联想Y410P。

Graphical Models, Exponential Families, and Variational Inference

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: * Collaborative filtering techniques that enable online retailers to recommend products or media * Methods of clustering to detect groups of similar items in a large dataset * Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm * Optimization algorithms that search millions of possible solutions to a problem and choose the best one * Bayesian filtering, used in spam filters for classifying documents based on word types and other features * Using decision trees not only to make predictions, but to model the way decisions are made * Predicting numerical values rather than classifications to build price models * Support vector machines to match people in online dating sites * Non-negative matrix factorization to find the independent features in a dataset * Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

SciPy is open-source software for mathematics, science, and engineering. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines. Together, they are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers.

What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

爬取了知乎上的美女图像，自动对颜值进行评分，过滤出高颜值。

武汉大学测绘遥感信息工程国家重点实验室复试笔试历年真题及答案

课程论文模板，简结明了，帮助你在此基础上获得高分。

脸谱网如何从默默无闻到坐拥二十几亿用户？ 爱彼迎、优步何以在短短时间估值超过百亿美元？ 领英怎样跨步成为全球领先的职业社交平台? 这些初创公司实现爆发式成长的共同奥秘就是增长黑客。 增长黑客是硅谷当下热门的新商业方法论，其精髓在于通过快节奏测试和迭代，以极低甚至零成本获取并留存用户。 作为最早提出“增长黑客”概念的理论先驱、带领Dropbox实现500%增长的实战领军人物，作者在书中分享了如何跨部门搭建增长黑客团队，以及实现用户和利润双增长的具体行动指南。该书一经出版，便被科技公司奉为运营圭臬。

基于C#写的遥感图像处理的课程设计程序，实现了影像读取，影像滤波，影像几何校正和影像分类，完美实现老师的要求。

基于Python的GPA计算器，可以直接通过导入exl表格读取信息，在你计算GPA，只需要按照实例表格写入自己的数据，就可以使用啦。