Download data mining and predictive analysis intelligence gathering and crime analysis in pdf or read data mining and predictive analysis intelligence gathering and crime analysis in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get data mining and predictive analysis intelligence gathering and crime analysis in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



Data Mining And Predictive Analysis

Author: Colleen McCue
Publisher: Butterworth-Heinemann
ISBN: 0128004088
Size: 77.46 MB
Format: PDF
View: 2894
Download and Read
Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis, and operational law enforcement settings. This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics in intelligence and security analysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment. Discusses new and emerging technologies and techniques, including up-to-date information on predictive policing, a key capability in law enforcement and security Demonstrates the importance of analytic context beyond software Covers new models for effective delivery of advanced analytics to the operational environment, which have increased access to even the most powerful capabilities Includes terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis

Data Mining And Predictive Analysis Intelligence Gathering And Crime Analysis

Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1497015758
Size: 75.83 MB
Format: PDF, Docs
View: 7184
Download and Read
Facts101 is your complete guide to Data Mining and Predictive Analysis, Intelligence Gathering and Crime Analysis. In this book, you will learn topics such as Applications, Case Examples, Advanced Concepts and Future Trends, plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Datenanalyse Mit Python

Author: Wes McKinney
Publisher: O'Reilly
ISBN: 3960102143
Size: 60.94 MB
Format: PDF, Mobi
View: 685
Download and Read
Erfahren Sie alles über das Manipulieren, Bereinigen, Verarbeiten und Aufbereiten von Datensätzen mit Python: Aktualisiert auf Python 3.6, zeigt Ihnen dieses konsequent praxisbezogene Buch anhand konkreter Fallbeispiele, wie Sie eine Vielzahl von typischen Datenanalyse-Problemen effektiv lösen. Gleichzeitig lernen Sie die neuesten Versionen von pandas, NumPy, IPython und Jupyter kennen.Geschrieben von Wes McKinney, dem Begründer des pandas-Projekts, bietet Datenanalyse mit Python einen praktischen Einstieg in die Data-Science-Tools von Python. Das Buch eignet sich sowohl für Datenanalysten, für die Python Neuland ist, als auch für Python-Programmierer, die sich in Data Science und Scientific Computing einarbeiten wollen. Daten und zugehöriges Material des Buchs sind auf GitHub verfügbar.Aus dem Inhalt:Nutzen Sie die IPython-Shell und Jupyter Notebook für das explorative ComputingLernen Sie Grundfunktionen und fortgeschrittene Features von NumPy kennenSetzen Sie die Datenanalyse-Tools der pandasBibliothek einVerwenden Sie flexible Werkzeuge zum Laden, Bereinigen, Transformieren, Zusammenführen und Umformen von DatenErstellen Sie interformative Visualisierungen mit matplotlibWenden Sie die GroupBy-Mechanismen von pandas an, um Datensätzen zurechtzuschneiden, umzugestalten und zusammenzufassenAnalysieren und manipulieren Sie verschiedenste Zeitreihen-DatenFür diese aktualisierte 2. Auflage wurde der gesamte Code an Python 3.6 und die neuesten Versionen der pandas-Bibliothek angepasst. Neu in dieser Auflage: Informationen zu fortgeschrittenen pandas-Tools sowie eine kurze Einführung in statsmodels und scikit-learn.

Predictive Analytics

Author: Eric Siegel
Publisher: John Wiley & Sons
ISBN: 1118416856
Size: 56.83 MB
Format: PDF, ePub, Docs
View: 7294
Download and Read
“Mesmerizing & fascinating...” —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive Analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated — and Hillary for America 2016 plans to calculate — the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 183 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.

Journeys To Data Mining

Author: Mohamed Medhat Gaber
Publisher: Springer Science & Business Media
ISBN: 3642280471
Size: 80.63 MB
Format: PDF, Docs
View: 3060
Download and Read
Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing. The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions: 1. What are your motives for conducting research in the data mining field? 2. Describe the milestones of your research in this field. 3. What are your notable success stories? 4. How did you learn from your failures? 5. Have you encountered unexpected results? 6. What are the current research issues and challenges in your area? 7. Describe your research tools and techniques. 8. How would you advise a young researcher to make an impact? 9. What do you predict for the next two years in your area? 10. What are your expectations in the long term? In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.

Wirtschaftsspionage Und Intelligence Gathering

Author: Alexander Tsolkas
Publisher: Springer-Verlag
ISBN: 3834886408
Size: 53.59 MB
Format: PDF
View: 4228
Download and Read
Im Wirtschaftskreislauf entstehend Datensammlungen. Darin werden Informationen über die wirtschaftliche Tätigkeit von Unternehmen gespeichert. Die Unternehmen haben aber keinen Einfluss auf die Generierung, Speicherung und Verwendung dieser Daten. Alexander Tsolkas und Friedrich Wimmer erklären anhand von Beispielen, wie diese Datensammlungen ausgespäht werden können, wie Unternehmen die eigene Gefährdungslage einschätzen und wie sie das Risiko durch Tarnen und Täuschen verringern können.

Getting Started With Business Analytics

Author: David Roi Hardoon
Publisher: CRC Press
ISBN: 1439896542
Size: 36.23 MB
Format: PDF, Mobi
View: 3320
Download and Read
Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.

Big Data Work

Author: Thomas H. Davenport
Publisher: Vahlen
ISBN: 3800648156
Size: 69.79 MB
Format: PDF, ePub, Docs
View: 6152
Download and Read
Big Data in Unternehmen. Dieses neue Buch gibt Managern ein umfassendes Verständnis dafür, welche Bedeutung Big Data für Unternehmen zukünftig haben wird und wie Big Data tatsächlich genutzt werden kann. Am Ende jedes Kapitels aktivieren Fragen, selbst nach Lösungen für eine erfolgreiche Implementierung und Nutzung von Big Data im eigenen Unternehmen zu suchen. Die Schwerpunkte - Warum Big Data für Sie und Ihr Unternehmen wichtig ist - Wie Big Data Ihre Arbeit, Ihr Unternehmen und Ihre Branche verändern - - wird - Entwicklung einer Big Data-Strategie - Der menschliche Aspekt von Big Data - Technologien für Big Data - Wie Sie erfolgreich mit Big Data arbeiten - Was Sie von Start-ups und Online-Unternehmen lernen können - Was Sie von großen Unternehmen lernen können: Big Data und Analytics 3.0 Der Experte Thomas H. Davenport ist Professor für Informationstechnologie und -management am Babson College und Forschungswissenschaftler am MIT Center for Digital Business. Zudem ist er Mitbegründer und Forschungsdirektor am International Institute for Analytics und Senior Berater von Deloitte Analytics.

Die Politik Der Gro En Zahlen

Author: Alain Desrosières
Publisher: Springer-Verlag
ISBN: 3540270116
Size: 13.10 MB
Format: PDF
View: 6682
Download and Read
Statistik ("Staatenkunde"), Wahrscheinlichkeitsrechnung und die Philosophie der Wahrscheinlichkeit sind auch als "siamesische Drillinge" bekannt. Das Buch analysiert den Werdegang der Statistik und zeigt Verbindungen zwischen der internalistischen Geschichte der Formalismen und Werkzeuge sowie der externalistisch orientierten Geschichte der Institutionen auf. Der Spannungsbogen erstreckt sich vom Vorabend der Französischen Revolution bis hin zum Ende des Zweiten Weltkriegs, wobei Frankreich, Deutschland, England und die USA ausführlich behandelt werden. Was haben Richter und Astronomen gemeinsam? Wer waren die "politischen Arithmetiker"? Was ist ein "Durchschnittsmensch"? Wie ändert sich im Laufe der Zeit das, was man "Realismus" nennt? Kann man vom Teil auf das Ganze schließen? Und wenn ja, warum? Welche Rolle spielt der Franziskanerorden? Wir begegnen Adolphe Quetelet, Karl Pearson, Egon Pearson, Francis Galton, Emile Durkheim und vielen anderen. Glücksspiele, Zufall, Bayesscher Ansatz, das St. Petersburger Paradoxon, der Choleravibrio, Erblichkeit, das Galtonsche Brett, Taxonomie, Wahlprognosen, Arbeitslosigkeit und Ungleichheit, die Entstehung der Arten, die Ordnung der Dinge und die Dinge des Lebens – das sind die Themen des Buches.