Modeling Techniques in Predictive Analytics with Python and by Thomas W. Miller

By Thomas W. Miller

grasp predictive analytics, from begin to end   commence with method and administration grasp equipment and construct versions rework your versions into highly-effective code—in either Python and R   This distinct e-book might help you employ predictive analytics, Python, and R to unravel genuine company difficulties and force genuine aggressive virtue. You’ll grasp predictive analytics via sensible case reports, intuitive facts visualizations, and updated code for either Python and R—not complicated math.   step-by-step, you’ll stroll via defining difficulties, picking info, crafting and optimizing types, writing potent Python and R code, studying effects, and extra. every one bankruptcy makes a speciality of considered one of today’s key functions for predictive analytics, providing talents and information to place types to work—and maximize their worth.   Thomas W. Miller, chief of Northwestern University’s pioneering application in predictive analytics, addresses every thing you must be triumphant: technique and administration, tools and versions, and know-how and code.   If you’re new to predictive analytics, you’ll achieve a powerful starting place for attaining actual, actionable effects. If you’re already operating within the box, you’ll grasp robust new abilities. If you’re accustomed to both Python or R, you’ll realize how those languages supplement one another, allowing you to do much more.   All information units, broad Python and R code, and extra examples to be had for obtain at http://www.ftpress.com/miller/   Python and R provide sizeable strength in predictive analytics, information technology, and massive information. This e-book may help you leverage that energy to unravel genuine company difficulties, and force genuine aggressive virtue.   Thomas W. Miller’s detailed balanced strategy combines enterprise context and quantitative instruments, illuminating each one procedure with conscientiously defined code for the newest types of Python and R. If you’re new to predictive analytics, Miller can provide a robust beginning for reaching actual, actionable effects. If you’re already a modeler, programmer, or supervisor, you’ll examine the most important talents you don’t have already got.   utilizing Python and R, Miller addresses a number of enterprise demanding situations, together with segmentation, model positioning, product selection modeling, pricing learn, finance, activities, textual content analytics, sentiment research, and social community research. He illuminates using cross-sectional info, time sequence, spatial, and spatio-temporal facts.   You’ll examine why every one challenge concerns, what information are appropriate, and the way to discover the information you’ve pointed out. Miller courses you thru conceptually modeling every one info set with phrases and figures; after which modeling it back with practical code that grants actionable insights.   You’ll stroll via version development, explanatory variable subset choice, and validation, gaining knowledge of most sensible practices for bettering out-of-sample predictive functionality. Miller employs information visualization and statistical portraits that can assist you discover facts, current versions, and assessment functionality. Appendices comprise 5 whole case reviews, and a close primer on glossy information technological know-how equipment.   Use Python and R to realize strong, actionable, ecocnomic insights approximately: ads and promoting purchaser choice and selection marketplace baskets and comparable purchases monetary forecasting Operations administration Unstructured textual content and language purchaser sentiment model and cost activities workforce functionality and lots more and plenty extra  

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R Deep Learning Essentials by Dr. Joshua F. Wiley

By Dr. Joshua F. Wiley

Key Features

  • Harness the power to construct algorithms for unsupervised facts utilizing deep studying strategies with R
  • Master the typical difficulties confronted comparable to overfitting of information, anomalous datasets, snapshot attractiveness, and function tuning whereas construction the models
  • Build types in terms of neural networks, prediction and deep prediction

Book Description

Deep studying is a department of computing device studying according to a collection of algorithms that try and version high-level abstractions in facts by utilizing version architectures. With the excellent reminiscence administration and the whole integration with multi-node enormous facts structures, the H2O engine has develop into a growing number of renowned between information scientists within the box of deep learning.

This booklet will introduce you to the deep studying package deal H2O with R and assist you comprehend the options of deep studying. we'll begin by way of constructing very important deep studying applications to be had in R after which circulate in the direction of development types on the topic of neural networks, prediction, and deep prediction, all of this with assistance from real-life examples.

After fitting the H2O package deal, you are going to know about prediction algorithms. relocating forward, recommendations equivalent to overfitting facts, anomalous facts, and deep prediction versions are defined. eventually, the booklet will hide recommendations in terms of tuning and optimizing models.

What you are going to learn

  • Set up the R package deal H2O to coach deep studying models
  • Understand the middle strategies in the back of deep studying models
  • Use Autoencoders to spot anomalous information or outliers
  • Predict or classify facts immediately utilizing deep neural networks
  • Build generalizable versions utilizing regularization to prevent overfitting the learning data

About the Author

Dr. Joshua F. Wiley is a lecturer at Monash collage and a senior companion at Elkhart team constrained, a statistical consultancy. He earned his PhD from the collage of California, la. His learn specializes in utilizing complicated quantitative how you can comprehend the advanced interplays of mental, social, and physiological approaches with regards to mental and actual wellbeing and fitness. In information and information technology, Joshua makes a speciality of biostatistics and is drawn to reproducible learn and graphical screens of information and statistical types. via consulting at Elkhart workforce constrained and his former paintings on the UCLA Statistical Consulting team, Joshua has helped a big selection of consumers, starting from skilled researchers to biotechnology businesses. He develops or codevelops a few R programs together with varian, a package deal to behavior Bayesian scale-location structural equation versions, and MplusAutomation, a well-liked package deal that hyperlinks R to the economic Mplus software.

Table of Contents

  1. Getting begun with Deep Learning
  2. Training a Prediction Model
  3. Preventing Overfitting
  4. Identifying Anomalous Data
  5. Training Deep Prediction Models
  6. Tuning and Optimizing Models
  7. Bibliography

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Fifty Years of Fuzzy Logic and its Applications (Studies in by Dan E. Tamir,Naphtali D. Rishe,Abraham Kandel

By Dan E. Tamir,Naphtali D. Rishe,Abraham Kandel

This booklet provides a accomplished record at the evolution of Fuzzy common sense for the reason that its formula in Lotfi Zadeh’s seminal paper on “fuzzy sets,” released in 1965. additionally, it encompasses a stimulating sampling from the huge box of study and improvement encouraged by means of Zadeh’s paper. The chapters, written through pioneers and renowned students within the box, convey how fuzzy units were effectively utilized to synthetic intelligence, regulate concept, inference, and reasoning. The e-book additionally stories on theoretical concerns; good points fresh functions of Fuzzy common sense within the fields of neural networks, clustering, facts mining and software program checking out; and highlights a tremendous paradigm shift as a result of Fuzzy common sense within the sector of uncertainty administration. Conceived via the editors as an educational social gathering of the fifty years’ anniversary of the 1965 paper, this paintings is a must have for college kids and researchers keen to get an inspiring photograph of the prospects, boundaries, achievements and accomplishments of Fuzzy Logic-based systems.

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Sentic Computing: Techniques, Tools, and Applications: 2 by Erik Cambria,Amir Hussain

By Erik Cambria,Amir Hussain

during this e-book logic computing recommendations are additional constructed and utilized to bridge the semantic hole among word-level typical language facts and the concept-level reviews conveyed through those. particularly, the ensemble software of graph mining and multi-dimensionality relief thoughts is exploited on logic wisdom bases to advance a unique clever engine for open-domain opinion mining and sentiment research. The proposed method, termed sentic computing, plays a clause-level semantic research of textual content, which permits the inference of either the conceptual and emotional details linked to traditional language reviews and, as a result, a extra effective passage from (unstructured) textual info to (structured) machine-processable data.

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Quality of Experience und Quality of Service im by Balzer

By Balzer

Der Autor gibt eine umfassende Übersicht der Konzepte für caliber of provider (QoS) und caliber of expertise im Mobilkommunikationsbereich, additionally die vom Endkunden wahrgenommene Qualität entsprechender Dienste und Funktionen, die Definition der Messgrößen und die praktische Umsetzung. Da Mobilfunk, insbesondere das cellular net, nicht nur einer der dynamischsten Technologiebereiche überhaupt, sondern auch Grundlage und zentrales point vieler Geschäftsmodelle in anderen Wachstumsbereichen ist, kommt diesem eine besondere Bedeutung zu. Erfolgsentscheidend ist, das Zusammenwirken von technischen Kenngrößen, Qualitätswahrnehmung und Kundenzufriedenheit zu verstehen und auf dieser foundation Investitionen optimum einzusetzen. Hierzu bietet das Buch wertvolle, praxisrelevante Orientierung.

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Data Mining and Statistics for Decision Making (Wiley Series by Stéphane Tufféry

By Stéphane Tufféry

information mining is the method of immediately looking huge volumes of information for types and styles utilizing computational suggestions from facts, computer studying and knowledge thought; it's the perfect instrument for such an extraction of data. facts mining is generally linked to a company or an organization's have to establish traits and profiles, permitting, for instance, shops to find styles on which to base advertising and marketing goals.

This ebook appears at either classical and up to date ideas of knowledge mining, akin to clustering, discriminant research, logistic regression, generalized linear versions, regularized regression, PLS regression, determination bushes, neural networks, help vector machines, Vapnik conception, naive Bayesian classifier, ensemble studying and detection of organization principles. they're mentioned in addition to illustrative examples during the publication to provide an explanation for the speculation of those tools, in addition to their strengths and limitations.

 Key Features:

  • Presents a finished creation to all thoughts utilized in info mining and statistical studying, from classical to most up-to-date techniques.
  • Starts from easy ideas as much as complicated concepts.
  • Includes many step by step examples with the most software program (R, SAS, IBM SPSS) in addition to a radical dialogue and comparability of these software.
  • Gives useful suggestions for info mining implementation to resolve actual international problems.
  • Looks at quite a number instruments and purposes, comparable to organization principles, net mining and textual content mining, with a distinct specialize in credits scoring.
  • Supported by means of an accompanying internet hosting datasets and consumer analysis. 

Statisticians and company intelligence analysts, scholars in addition to computing device technological know-how, biology, advertising and monetary danger pros in either advertisement and executive corporations throughout all enterprise and sectors will reap the benefits of this book.

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Marketing Data Science: Modeling Techniques in Predictive by Thomas W. Miller

By Thomas W. Miller

Now , a pacesetter of Northwestern University's prestigious analytics application offers a fully-integrated therapy of either the enterprise and educational parts of promoting purposes in predictive analytics. Writing for either managers and scholars, Thomas W. Miller explains crucial innovations, ideas, and idea within the context of real-world applications.

 

Building on Miller's pioneering application, Marketing information Science completely addresses segmentation, objective advertising and marketing, model and product positioning, new product improvement, selection modeling, recommender structures, pricing examine, retail web site choice, call for estimation, revenues forecasting, purchaser retention, and lifelong worth analysis.

 

Starting the place Miller's widely-praised Modeling innovations in Predictive Analytics left off, he integrates the most important details and insights that have been formerly segregated in texts on internet analytics, community technology, details know-how, and programming. insurance includes:

  • The function of analytics in providing potent messages at the web
  • Understanding the net by way of realizing its hidden structures
  • Being famous on the internet – and observing your individual competitors
  • Visualizing networks and realizing groups inside them
  • Measuring sentiment and making recommendations
  • Leveraging key information technological know-how tools: databases/data practise, classical/Bayesian records, regression/classification, computing device studying, and textual content analytics

Six whole case stories tackle exceedingly suitable concerns similar to: isolating valid e mail from junk mail; deciding on legally-relevant details for lawsuit discovery; gleaning insights from nameless internet browsing info, and extra. This text's wide set of net and community difficulties draw on wealthy public-domain info resources; many are observed by way of strategies in Python and/or R.


Marketing info Science can be a useful source for all scholars, school, agents who are looking to use company analytics to enhance advertising performance.

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Frank Kane's Taming Big Data with Apache Spark and Python by Frank Kane

By Frank Kane

Key Features

  • Understand how Spark should be disbursed throughout computing clusters
  • Develop and run Spark jobs successfully utilizing Python
  • A hands-on educational via Frank Kane with over 15 real-world examples educating you immense information processing with Spark

Book Description

Frank Kane's Taming colossal information with Apache Spark and Python is your spouse to studying Apache Spark in a hands-on demeanour. Frank will commence you off by means of educating you ways to establish Spark on a unmarried method or on a cluster, and you may quickly stream directly to reading huge facts units utilizing Spark RDD, and constructing and operating powerful Spark jobs speedy utilizing Python.

Apache Spark has emerged because the subsequent giant factor within the colossal information area – speedy emerging from an ascending expertise to a longtime celebrity in precisely an issue of years. Spark lets you quick extract actionable insights from quite a lot of info, on a real-time foundation, making it a vital instrument in lots of glossy businesses.

Frank has packed this e-book with over 15 interactive, fun-filled examples correct to the true international, and he'll empower you to appreciate the Spark environment and enforce production-grade real-time Spark initiatives with ease.

What you are going to learn

  • Find out how one can establish large information difficulties as Spark problems
  • Install and run Apache Spark in your machine or on a cluster
  • Analyze huge facts units throughout many CPUs utilizing Spark's Resilient allotted Datasets
  • Implement computing device studying on Spark utilizing the MLlib library
  • Process non-stop streams of information in genuine time utilizing the Spark streaming module
  • Perform complicated community research utilizing Spark's GraphX library
  • Use Amazon's Elastic MapReduce provider to run your Spark jobs on a cluster

About the Author

My identify is Frank Kane. I spent 9 years at Amazon and IMDb, wrangling hundreds of thousands of purchaser scores and shopper transactions to supply issues akin to custom-made concepts for videos and items and "people who received this additionally bought." I inform you, I want we had Apache Spark again then, whilst I spent years attempting to remedy those difficulties there. I carry 17 issued patents within the fields of disbursed computing, facts mining, and laptop studying. In 2012, I left to begin my very own winning corporation, Sundog software program, which makes a speciality of digital truth setting know-how, and educating others approximately vast info analysis.

Table of Contents

  1. Getting all started with Spark
  2. Spark fundamentals and straightforward Examples
  3. Advanced Examples of Spark Programs
  4. Running Spark on a Cluster
  5. SparkSQL, Dataframes and Datasets
  6. Other Spark applied sciences and Libraries
  7. Where to head From right here? - studying extra approximately Spark and information Science

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Practical Approaches to Causal Relationship Exploration by Jiuyong Li,Lin Liu,Thuc Duy Le

By Jiuyong Li,Lin Liu,Thuc Duy Le

This short provides 4 useful how to successfully discover causal relationships, that are usually used for rationalization, prediction and choice making in drugs, epidemiology, biology, economics, physics and social sciences. the 1st tools observe conditional independence exams for causal discovery. The final tools hire organization rule mining for effective causal speculation new release, and a partial organization attempt and retrospective cohort learn for validating the hypotheses. All 4 tools are cutting edge and potent in choosing capability causal relationships round a given aim, and every has its personal energy and weak point. for every procedure, a software program software is supplied besides examples demonstrating its use. sensible techniques to Causal courting Exploration is designed for researchers and practitioners operating within the parts of man-made intelligence, computing device studying, info mining, and biomedical examine. the fabric additionally advantages complicated scholars attracted to causal courting discovery.

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Advances in Machine Learning and Data Analysis: 48 (Lecture by Mahyar Amouzegar

By Mahyar Amouzegar

A huge overseas convention on Advances in computer studying and information research was once held in UC Berkeley, California, united states, October 22-24, 2008, less than the auspices of the area Congress on Engineering and desktop technology (WCECS 2008). This quantity includes 16 revised and prolonged study articles written through widespread researchers partaking within the convention. subject matters coated contain specialist procedure, clever determination making, Knowledge-based structures, wisdom extraction, information research instruments, Computational biology, Optimization algorithms, scan designs, complicated process id, Computational modeling, and commercial purposes. Advances in desktop studying and knowledge Analysis deals the cutting-edge of super advances in computer studying and information research and in addition serves as a good reference textual content for researchers and graduate scholars, engaged on computer studying and information analysis.

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