Machine Learning for Hackers 作者: Drew Conway,John Myles White出版社/メーカー: Oreilly & Associates Inc発売日: 2012/02/28メディア: ペーパーバック クリック: 63回この商品を含むブログを見る 機械学習の評価方法について学習 機械学習初心者ですが最近業務で本格的に触り始めています。少し前までSmartPhoneのWebAppliを作ることを専門職としていたので機械学習の領域は未知な事が非常に多く、用語の意味ですら十分に理解できていません。今日は機械学習の評価方法を中心に学習(勉強)した内容を記録して行きます。例えばPrecision/Accuracy/Recallの言葉の違いやROC曲線,AUC評価などの技法といったものが話の中心になります。初心者視点で書いていますので専門性がありません。間
What is MLN? MLN (Manage Large Networks) is a virtual machine administration tool designed to build and run virtual machine networks based on Xen, VMware Server and User-Mode Linux. It is ideal for creating virtual network labs for education, testing, hosting or simply playing around with virtual machines. Get the latest MLN release: wget http://mln.sourceforge.net/files/mln-latest.tar.gz tar xzf
Spring 2012 Foundations of Machine Learning Course#: CSCI-GA.2566-001 Instructor: Mehryar Mohri Graders/TAs: Umar Syed and Afshin Rostami Mailing List Course Description This course introduces the fundamental concepts and methods of machine learning, including the description and analysis of several modern algorithms, their theoretical basis, and the illustration of their applications. Many of the
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The Recovery-Oriented Computing (ROC) project is a joint Berkeley/Stanford research project that is investigating novel techniques for building highly-dependable Internet services. In a significant divergence from traditional fault-tolerance approaches, ROC emphasizes recovery from failures rather than failure-avoidance. This philosophy is motivated by the observation that even the most robust sy
Large data sets are increasingly common in cloud and virtualized environments. For example, transfers of multiple gigabytes are commonplace, as are replicated blocks of such sizes. There is a need for fast error-correction or data reconciliation in such settings even when the expected number of errors is small. Motivated by such cloud reconciliation problems, we consider error-correction schemes d
Oliver Reichenstein is the founder and director of Information Architects, the Tokyo, Zurich, and Berlin-based design agency. iA's usual trade is website design and consultancy along with the odd concept like the Twitter strikethrough, but the company has also found recent success in iOS and Mac app development. Writer for iPad is a pioneering minimalist text editor, and its focus-enhancing combin
current edition The book is here. It is 253 pages. Contents Introduction Basic Theories Basic Data Structures Function Theory Program Theory Programming Language Recursive Definition Theory Design and Implementation Concurrency Interaction Exercises Reference symbols pages 234 through 246 (laws etc.) for printing solutions to exercises change log 中文版 (Chinese 2018 version) The course Formal Method
Welcome to the ACL2 home page! We highlight a few aspects of ACL2: Libraries (Books). Libraries of books (files containing definitions and theorems) extend the code that we have written. In particular, the distribution tarball includes the community books, which are contributed and maintained by the members of the ACL2 community. Documentation. There is an extensive user's manual for the ACL2 syst
This article is about mathematical analysis of computing. For associated folklore and broad implications of the theorem, see No free lunch theorem. The problem is to rapidly find a solution among candidates a, b, and c that is as good as any other, where goodness is either 0 or 1. There are eight instances ("lunch plates") fxyz of the problem, where x, y, and z indicate the goodness of a, b, and c
Updated (February 07 2013): If you enjoy this article, you may also find the more academically-inclined article The Impact of Meta-Tracing on VM Design and Implementation interesting. [This is a long article because it covers a lot of ground that is little known by the computing mainstream, and easily misunderstood. If you’re familiar with the area, you may find yourself wanting to skip certain ex
情報検索とパターン照合（７回）（喜田が担当） ガイダンス、および、準備 講義スライド Prefix型アルゴリズム（naïve、KMP、AC、Shift-And/Or） 講義スライド Suffix型アルゴリズム（BM、Galil、Horspool、Sundayほか） 講義スライド 近似文字列照合 講義スライド 正規表現の照合 講義スライド 圧縮テキスト上のパターン照合 講義スライド 文字列照合技術の今後 講義スライド
Machine Learning video segments by topic - Professor Yaser Abu-Mostafa Aggregation Overview of ensemble learning (boosting, blending, before and after the fact) Bayesian Learning Validity of the Bayesian approach (prior, posterior, unknown versus probabilistic) Bias-Variance Tradeoff Basic derivation (overfit and underfit, approximation-generalization tradeoff) Example (sinusoidal target function)
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