Angebote zu "Filtering" (85 Treffer)

Kategorien

Shops

Machine Learning
73,99 € *
ggf. zzgl. Versand

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods. The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling. Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied. MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.

Anbieter: buecher
Stand: 24.02.2020
Zum Angebot
Machine Learning
73,99 € *
ggf. zzgl. Versand

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods. The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling. Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied. MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.

Anbieter: buecher
Stand: 24.02.2020
Zum Angebot
Frustrated with Yelp?!: The Business Owner's Gu...
9,95 € *
ggf. zzgl. Versand

Are you frustrated with Yelp.com? Wondering why Yelp is filtering your good reviews? For many small business owners, that's like asking if the sky is blue or if taxes stink! But it doesn't have to be that way. By the time you finish listening to Frustrated with Yelp!?, you will have learned all the tricks to employ and all the pitfalls to avoid while establishing your business's positive, relevant presence on Yelp.com. Yelp is one of the most powerful social media tools today's tech savvy consumer uses, and it can be the greatest generator of business for the business that "uses" Yelp properly. Just so, the business owner who takes the wrong approach with Yelp.com (or, even worse, those who don't engage with the website at all) can stand to suffer a tarnished reputation and loss of customers and profits! Frustrated with Yelp!? will help introduce Yelp.com to the uninitiated, explaining what exactly the site is, how it works, and who tends to use it. This book will take you through the basics, such as how to set up your business account on Yelp.com, or how to "claim" a page already established for your business. You will learn how to make sure your business' Yelp profile is accurate and up to date, and how to add, change, or remove information, images, and other pertinent material. You will also get something of a "behind the scenes" look at how and why Yelp.com operates the way it does, with the infamous, mysterious Yelp Filter explained. Most important of all, though, you will be getting a filed manual on how to deal with bad reviews and unhappy reviewers, and you will learn how to engage with and leverage satisfied clientele, reducing the negative impact created by the former group and maximizing the positive impact generated by the latter. Through narrative chapters, step-by-step instructions, and even cautionary case studies, you can gain great insight and experience on how to best use Yelp.com. 1. Language: English. Narrator: Steven Bateman. Audio sample: http://samples.audible.de/bk/acx0/009001/bk_acx0_009001_sample.mp3. Digital audiobook in aax.

Anbieter: Audible
Stand: 24.02.2020
Zum Angebot
Probability with R
113,99 € *
ggf. zzgl. Versand

Provides a comprehensive introduction to probability with an emphasis on computing-related applications This self-contained new and extended edition outlines a first course in probability applied to computer-related disciplines. As in the first edition, experimentation and simulation are favoured over mathematical proofs. The freely down-loadable statistical programming language R is used throughout the text, not only as a tool for calculation and data analysis, but also to illustrate concepts of probability and to simulate distributions. The examples in Probability with R: An Introduction with Computer Science Applications, Second Edition cover a wide range of computer science applications, including: testing program performance; measuring response time and CPU time; estimating the reliability of components and systems; evaluating algorithms and queuing systems. Chapters cover: The R language; summarizing statistical data; graphical displays; the fundamentals of probability; reliability; discrete and continuous distributions; and more. This second edition includes: improved R code throughout the text, as well as new procedures, packages and interfaces; updated and additional examples, exercises and projects covering recent developments of computing; an introduction to bivariate discrete distributions together with the R functions used to handle large matrices of conditional probabilities, which are often needed in machine translation; an introduction to linear regression with particular emphasis on its application to machine learning using testing and training data; a new section on spam filtering using Bayes theorem to develop the filters; an extended range of Poisson applications such as network failures, website hits, virus attacks and accessing the cloud; use of new allocation functions in R to deal with hash table collision, server overload and the general allocation problem. The book is supplemented with a Wiley Book Companion Site featuring data and solutions to exercises within the book. Primarily addressed to students of computer science and related areas, Probability with R: An Introduction with Computer Science Applications, Second Edition is also an excellent text for students of engineering and the general sciences. Computing professionals who need to understand the relevance of probability in their areas of practice will find it useful.

Anbieter: buecher
Stand: 24.02.2020
Zum Angebot
Probability with R
113,99 € *
ggf. zzgl. Versand

Provides a comprehensive introduction to probability with an emphasis on computing-related applications This self-contained new and extended edition outlines a first course in probability applied to computer-related disciplines. As in the first edition, experimentation and simulation are favoured over mathematical proofs. The freely down-loadable statistical programming language R is used throughout the text, not only as a tool for calculation and data analysis, but also to illustrate concepts of probability and to simulate distributions. The examples in Probability with R: An Introduction with Computer Science Applications, Second Edition cover a wide range of computer science applications, including: testing program performance; measuring response time and CPU time; estimating the reliability of components and systems; evaluating algorithms and queuing systems. Chapters cover: The R language; summarizing statistical data; graphical displays; the fundamentals of probability; reliability; discrete and continuous distributions; and more. This second edition includes: improved R code throughout the text, as well as new procedures, packages and interfaces; updated and additional examples, exercises and projects covering recent developments of computing; an introduction to bivariate discrete distributions together with the R functions used to handle large matrices of conditional probabilities, which are often needed in machine translation; an introduction to linear regression with particular emphasis on its application to machine learning using testing and training data; a new section on spam filtering using Bayes theorem to develop the filters; an extended range of Poisson applications such as network failures, website hits, virus attacks and accessing the cloud; use of new allocation functions in R to deal with hash table collision, server overload and the general allocation problem. The book is supplemented with a Wiley Book Companion Site featuring data and solutions to exercises within the book. Primarily addressed to students of computer science and related areas, Probability with R: An Introduction with Computer Science Applications, Second Edition is also an excellent text for students of engineering and the general sciences. Computing professionals who need to understand the relevance of probability in their areas of practice will find it useful.

Anbieter: buecher
Stand: 24.02.2020
Zum Angebot
Personalized News Filtering and Recommendation ...
61,90 € *
ggf. zzgl. Versand

In this work, a study of personalized news filtering and recommendation systems is presented. An advance K-NN algorithm and its applicability in solving recommendation problems is proposed, a Chi-square statistics based (X2SB) version of the K-NN algorithm is proposed. The new X2SB-KNN algorithm can reduce run-time and increases execution speeds through the use of critical X2 value. The recommendation system can overcome scalability problem through Real-Time pattern discovery and online pattern matching. It can also alleviate information overloading and computational complexity problems common with many existing recommendation algorithms. A novel feature selection technique called Fuzzy expert based (FEB) feature selection technique is also proposed, this method is used at data pre-processing stage to select the best feature for the classification and recommendation system. An In-house Java program was developed to implement the (X2SB-KNN) classifier on an experimental website. Performance comparison between the proposed system, the Euclidean distance K-NN and Naïve Bayesian methods shows that the (X2SB-KNN) classifier can outperform the other methods studied.

Anbieter: Dodax
Stand: 24.02.2020
Zum Angebot
Dynamic Recommender System
55,90 € *
ggf. zzgl. Versand

One of the foremost challenges web information systems currently confront is the effective management of large volume of documents. There is an urgent need to provide easy and swift access to the information that satisfies the needs of consumers on the web. To handle this problem web developers have focused on building information filtering systems known as Recommender Systems. Recommender Systems are the tools that assist user in navigating through the huge amount of information available on the internet. They have become an essential component of every website on the internet particularly those relating to e-commerce. However, changing user requirements pose a huge challenge in developing accurate Recommender System. Recent studies demonstrate that temporal information can play an important role in the working of Recommender System when they are deployed in dynamic real world setting. In this book, we look specifically at how to utilize temporal information as an additional input in Recommender System and provide accurate and scalable recommendations. The work focuses on the dynamics of changing user requirements with time.

Anbieter: Dodax
Stand: 24.02.2020
Zum Angebot
URL Filtering in BroadBand Access Technologies ...
54,90 € *
ggf. zzgl. Versand

Information and communication technology has always fascinated me and this interest was the main reason behind my decision to opt for a degree in software engineering. During the course of my studies my interest grew towards the security of these systems, leading me to choose for specialization in security. I made a decision to undertake courses that will broaden my knowledge in system security and therefore enrolled in Network Security, Digital Forensics, Cryptography and System incident handling courses. After taking courses of my degree, self study and team projects, I gained a deeper and valuable knowledge of system security and decided to take my final year project on URL filtering in broadband access technologies. The project focused on the content based filtering of websites. A novel method was introduced to block a specific text based content of the webpage instead blocking full website, in addition to this an additional feature to filter out URLs based on server policy was implemented. This book is the publication of My work along with my team members Sana Fatima and Saad Abdullah who pro-actively helped me and co operated with me to complete this work.

Anbieter: Dodax
Stand: 24.02.2020
Zum Angebot
Websense
29,00 € *
ggf. zzgl. Versand

High Quality Content by WIKIPEDIA articles! Websense is a San Diego-based company specializing in Web security gateway software. It enables clients (businesses and governments) to block access to chosen categories of website. It has come under criticism from civil liberties groups on the grounds that it assists repressive regimes to restrict freedom of speech.Websense was founded by Phil Trubey in 1994. It went public in the year 2000.Apart from Web filtering, also known as Internet content-control software, the company provides email security, and data loss-prevention technology. The software also tracks individual internet usage, and its reports can be date drilled by "risk class, category, URL, application, user, workstation, dates, and more."

Anbieter: Dodax
Stand: 24.02.2020
Zum Angebot