Python machine learning

EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques.

This book is intended to provide a systematic overview of so-called smart techniques, such as nature-inspired algorithms, machine learning and metaheuristics. Despite their ubiquitous presence and wid

The workbook / project manual is designed to help you master key chapter content and apply it in the machine shop. This resource includes review material, plus guided practice operations and projects.

本書的主要目標是，大家一起來「不寫程式，而學AI」。例如不知Python而亦能用TensorFlow。 當今的AI是屬於機器學習(Machine Learning)的一支，基於神經網路( NN: Neural Network)的深度學習。現在，人人都想去理解AI電腦(即機器)到底是如何學習的，以便掌握AI技術熱潮，捷足先登，踏進這項當今的主流產業(AI人工智慧)。 然而，AI機器學習的演算法(Algorithm)又非常依賴於高等數學的運算式，包括線性、非線性函數、N維矩陣(Array)、張量(Tensor)、微分導數、梯度(Gradient)下降、梯度消失等大家很陌生的數學概念和術語。這些複雜性大大阻礙人人親近AI的機會和途徑。俗語說：「面對複雜，唯有簡單」。所以，尋覓和創造一個簡單、親切的途徑，讓人人都能享受，就能彌平進入AI的高大門檻了。Google推出的AI平台：TensorFlow。雖然它還不能完全實踐的美好境界，但可望它是一個不錯的起點了。於是，本書就將Excel試算表與TensorFlow結合起來，就能實現了。不懂程式設計而能學AI，好比不懂車而能學開車。在本書裡，筆者把與分離開來。於是大多數不諳編程技術者，皆能直接切入，而輕鬆愉快地學習AI了。

深度學習（Deep Learning）如今已成為非常活躍的研究領域，同時也為現代機器學習鋪展了一條康莊大道。本書提供許多範例與清楚的說明，引導讀者進一步了解這個複雜領域中的一些主要概念。包括Google、微軟和Facebook這樣的業界龍頭，全都在其內部積極發展深度學習團隊。不過對於一般人來說，深度學習仍舊是個相當複雜而困難的主題。如果您熟悉Python，並具備微積分的背景知識，加上對於機器學習的

This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the co

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern re

本書作者曾在北美多家智能專業公司任高級架構師，有20年數據挖掘、機器學習方面的設計、開發、管理經驗。他結合自己多年的行業經歷，總結了自己在機器學習方面的知識和實際工程中的經驗，提供了大量一線資料。本書不僅介紹了機器學習中的常用算法，而且給出了具體實施環境和經驗總結。重點介紹了相關算法，包括：相關因子算法、聚類算法、分類算法、回歸與測試算法等。不僅列舉了詳細示例，還介紹了算法在工程實踐中的具體應用，

The proceedings of DOSFIAC 2017 consist of papers on topics such as artificial intelligence, machine learning, big data, cloud computing, IOT, smart reservoir, visualization, GIS and SCADA systems. Th

Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is u

The problems it addresses include emotion representation, annotation of music excerpts, feature extraction, and machine learning. The book chiefly focuses on content-based analysis of music files, a s

你要聽特斯拉馬斯克的或是臉書祖克伯的？前者認為人工智慧（AI）會毁滅人類，後者說不會！其實你應聽Google的，它提供平台讓中小企業也可以搭上人工智慧的特快車！ 將衝擊世界的人工智慧類型基本上是指會自己學習的電腦，也就是所謂的機器學習（Machine Learning）及深度學習（Deep learning），而非過去大家習慣的電腦依程式行事。前者是指機器自己由大量資料中，得出某結論，如給電腦一堆

Python與機器學習這一話題是如此的寬廣，僅靠一本書自然不可能涵蓋到方方面面，甚至即使出一個系列也難能做到這點。單就機器學習而言，其領域就包括但不限於如下：有監督學習（Supervised Learning），無監督學習（Unsupervised Learning）和半監督學習（Semi-Supervised Learning）。而具體的問題又大致可以分兩類：分類問題（Classificatio

Learn how today’s businesses can transform themselves by leveraging real-time data and advanced machine learning analytics. This book provides prescriptive guidance for architects and develo

In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a s

★CNN、《新科學人》、《經濟學人》、《柯克斯書評》等多家媒體推薦報導★比爾．蓋茲年度選書！揭開大數據、人工智慧、機器學習的祕密，打造人類文明史上最強大的科技——終極演算法！有一個終極演算法，可以解開宇宙所有的祕密，現在大家都在競爭，誰能最先解開它！．機器學習是什麼？大演算又是什麼？．大演算如何運作與發展，機器可以預測什麼？．我們可以信任機器學過的東西嗎？．商業、政治為什麼要擁抱機器學習？．不只商

內容簡介:「本書提供許多絕佳的機器學習實用案例。有別於工具書或理論證明，本書著重於實際問題處理，因此具備程式設計背景及對機器學習有興趣的讀者們均可輕鬆入門。」 - Max Shron, OkCupid 如果你是平時喜歡上網蒐集各種資料的程式設計師，想尋找並學習資料分析的方法與工具，本書將會是您了解機器學習最好的起點。在Machine Learning領域中，包含各種分析問題的工具與方法，可以讓我們

The goal of structured prediction is to build machine learning models that predictrelational information that itself has structure, such as being composed of multiple interrelatedparts. These models,

Industrial Strength Empirical Modeling clearly explains the main principles of the different machine learning approaches and offers a methodology of how to integrate these techniques for successful r

This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techn

Packed with detailed examples and illustrations, PRECISION MACHINING TECHNOLOGY, 2e delivers the ideal introduction to today's machine tool industry, equipping readers with a solid understanding of fu

The Sony NEX-7 is one of the most innovative cameras Sony has ever introduced. It is the flagship of Sony's NEX product line, a whole new type of picture-taking machine, combining a tiny, mirrorless b

Boosting is an approach to machine learning based on the idea of creating a highlyaccurate predictor by combining many weak and inaccurate "rules of thumb." A remarkablyrich theory has evolved around

That Monday afternoon, in high-school gyms across America, kids were battling for the only glory American culture seems to want to dispense to the young these days: sports glory.? But at Dos Pueblos High School in Goleta, California, in a gear-cluttered classroom, a different type of “cool” was brewing.? A physics teacher with a dream – the first public high-school teacher ever to win a MacArthur Genius Award -- had rounded up a band of high-I.Q. students who wanted to put their technical know-how to work.? If you asked these brainiacs what the stakes were that first week of their project, they’d have told you it was all about winning a robotics competition – building the ultimate robot and prevailing in a machine-to-machine contest in front of 25,000 screaming fans at Atlanta’s Georgia Dome.?But for their mentor, Amir Abo-Shaeer, much more hung in the balance. ?The fact was, Amir had in mind a different vision for education, one based not on rote learning -- on absorbing facts and fig

Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms。 Specifically， the book distinguishes the inner nature

Machine learning develops intelligent computer systems that are able to generalizefrom previously seen examples. A new domain of machine learning, in which the prediction mustsatisfy the additional co

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure. Machine learning develops intelligent computer systems that are able to genera

The minimum description length (MDL) principle is a powerful method of inductive inference, the basis of statistical modeling, pattern recognition, and machine learning. It holds that the best explan

SQL，是關聯式資料庫的通用語。它是種不太獨立、與其他程式語言（如 C++、Java、Python與Perl）息息相關的語言。關聯式資料庫現在已普遍存在，使用者們至少該有些關於這種語言的知識。重要內容包括： ＊一口氣向很多個資料表收集與回傳關聯性資訊。這稱為聯結（join），是SQL 的運作核心。 ＊採用集合導向的資料操作方式。SQL 幾乎都是集合的操作，如果不好好利用這項優勢，就等於錯失SQ

The process of inductive inference -- to infer general laws and principles from particular instances -- is the basis of statistical modeling, pattern recognition, and machine learning. The Minimum Des

Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recog

This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an excit

Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the re

A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, s