Predictive Analytics a Complete Guide - 2019 Edition

Predictive Analytics a Complete Guide - 2019 Edition
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 304
Release: 2018-12-21
Genre:
ISBN: 9780655518884

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What are the output interfaces to external systems? What is the most important factor in vendor selection? What is tacit permission and approval to you? What is the share of fixed costs in the total costs per vehicle? How fast can you adapt to changes in the data stream? This breakthrough Predictive Analytics self-assessment will make you the accepted Predictive Analytics domain authority by revealing just what you need to know to be fluent and ready for any Predictive Analytics challenge. How do I reduce the effort in the Predictive Analytics work to be done to get problems solved? How can I ensure that plans of action include every Predictive Analytics task and that every Predictive Analytics outcome is in place? How will I save time investigating strategic and tactical options and ensuring Predictive Analytics costs are low? How can I deliver tailored Predictive Analytics advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Predictive Analytics essentials are covered, from every angle: the Predictive Analytics self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Predictive Analytics outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Predictive Analytics practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Predictive Analytics are maximized with professional results. Your purchase includes access details to the Predictive Analytics self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Predictive Analytics Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Fundamentals of Machine Learning for Predictive Data Analytics, second edition

Fundamentals of Machine Learning for Predictive Data Analytics, second edition
Author: John D. Kelleher
Publisher: MIT Press
Total Pages: 853
Release: 2020-10-20
Genre: Computers
ISBN: 0262361108

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The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Predictive Analytics for Human Resources

Predictive Analytics for Human Resources
Author: Jac Fitz-enz
Publisher: John Wiley & Sons
Total Pages: 180
Release: 2014-07-28
Genre: Business & Economics
ISBN: 1118893670

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Create and run a human resource analytics project with confidence For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: "Where do I start?" and "What tools are available?" Predictive Analytics for Human Resources is designed to answer these and other vital questions. The book explains the basics of every business—the vision, the brand, and the culture, and shows how predictive analytics supports them. The authors put the focus on the fundamentals of predictability and include a framework of logical questions to help set up an analytic program or project, then follow up by offering a clear explanation of statistical applications. Predictive Analytics for Human Resources is a how-to guide filled with practical and targeted advice. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, this important resource addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor. In the book, you'll find: A comprehensive guide to developing and implementing a human resource analytics project Illustrative examples that show how to go to market, develop a leadership model, and link it to financial targets through causal modeling Explanations of the ten steps required in building an analytics function How to add value through analysis of systems such as staffing, training, and retention For anyone who wants to launch an analytics project or program for HR, this complete guide provides the information and instruction to get started the right way.

Predictive Analysis A Complete Guide - 2019 Edition

Predictive Analysis A Complete Guide - 2019 Edition
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 308
Release: 2019-07-10
Genre:
ISBN: 9780655818274

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What would you recommend your friend do if he/she were facing this dilemma? What types of data do your Predictive Analysis indicators require? Which issues are too important to ignore? When a disaster occurs, who gets priority? How are training requirements identified? This astounding Predictive Analysis self-assessment will make you the entrusted Predictive Analysis domain visionary by revealing just what you need to know to be fluent and ready for any Predictive Analysis challenge. How do I reduce the effort in the Predictive Analysis work to be done to get problems solved? How can I ensure that plans of action include every Predictive Analysis task and that every Predictive Analysis outcome is in place? How will I save time investigating strategic and tactical options and ensuring Predictive Analysis costs are low? How can I deliver tailored Predictive Analysis advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Predictive Analysis essentials are covered, from every angle: the Predictive Analysis self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Predictive Analysis outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Predictive Analysis practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Predictive Analysis are maximized with professional results. Your purchase includes access details to the Predictive Analysis self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Predictive Analysis Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Predictive Analytics for the Modern Enterprise

Predictive Analytics for the Modern Enterprise
Author: Nooruddin Abbas Ali
Publisher: "O'Reilly Media, Inc."
Total Pages: 358
Release: 2024-05-20
Genre: Computers
ISBN: 1098136829

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The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow

Analytics Tools A Complete Guide - 2019 Edition

Analytics Tools A Complete Guide - 2019 Edition
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 304
Release: 2019-07-07
Genre:
ISBN: 9780655815778

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Is your organization using automated predictive analytics tools? Do you know the customers context? How important is machine data to your organizations ability to meet its goals? What will customers want in the future? For social media in a business context what differences are there between social media monitoring text analytics and predictive analytics tools? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Analytics Tools investments work better. This Analytics Tools All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Analytics Tools Self-Assessment. Featuring 936 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Analytics Tools improvements can be made. In using the questions you will be better able to: - diagnose Analytics Tools projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Analytics Tools and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Analytics Tools Scorecard, you will develop a clear picture of which Analytics Tools areas need attention. Your purchase includes access details to the Analytics Tools self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Analytics Tools Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Hands-On Predictive Analytics with Python

Hands-On Predictive Analytics with Python
Author: Alvaro Fuentes
Publisher: Packt Publishing Ltd
Total Pages: 320
Release: 2018-12-28
Genre: Computers
ISBN: 1789134544

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Step-by-step guide to build high performing predictive applications Key FeaturesUse the Python data analytics ecosystem to implement end-to-end predictive analytics projectsExplore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanationsLearn to deploy a predictive model's results as an interactive applicationBook Description Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming. What you will learnGet to grips with the main concepts and principles of predictive analyticsLearn about the stages involved in producing complete predictive analytics solutionsUnderstand how to define a problem, propose a solution, and prepare a datasetUse visualizations to explore relationships and gain insights into the datasetLearn to build regression and classification models using scikit-learnUse Keras to build powerful neural network models that produce accurate predictionsLearn to serve a model's predictions as a web applicationWho this book is for This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this exciting field will greatly benefit from reading this book. All you need is to be proficient in Python programming and have a basic understanding of statistics and college-level algebra.

A General Introduction to Data Analytics

A General Introduction to Data Analytics
Author: João Moreira
Publisher: John Wiley & Sons
Total Pages: 352
Release: 2018-07-18
Genre: Mathematics
ISBN: 1119296242

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A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.

Predictive Consumer Data Analytics a Complete Guide - 2019 Edition

Predictive Consumer Data Analytics a Complete Guide - 2019 Edition
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 314
Release: 2019-03-18
Genre:
ISBN: 9780655539599

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Modeling indirect effects of paid search advertising: which keywords lead to more future visits? Does the in situ hardware have the computational capacity to support such algorithms? Quality vs. Quantity: What data are required to satisfy the given value proposition? Quantity: What data are required to satisfy the given value proposition? How much has the customer spent on product purchases (monetary value)? This breakthrough Predictive Consumer Data Analytics self-assessment will make you the assured Predictive Consumer Data Analytics domain specialist by revealing just what you need to know to be fluent and ready for any Predictive Consumer Data Analytics challenge. How do I reduce the effort in the Predictive Consumer Data Analytics work to be done to get problems solved? How can I ensure that plans of action include every Predictive Consumer Data Analytics task and that every Predictive Consumer Data Analytics outcome is in place? How will I save time investigating strategic and tactical options and ensuring Predictive Consumer Data Analytics costs are low? How can I deliver tailored Predictive Consumer Data Analytics advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Predictive Consumer Data Analytics essentials are covered, from every angle: the Predictive Consumer Data Analytics self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Predictive Consumer Data Analytics outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Predictive Consumer Data Analytics practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Predictive Consumer Data Analytics are maximized with professional results. Your purchase includes access details to the Predictive Consumer Data Analytics self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Predictive Consumer Data Analytics Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)

HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)
Author: Harvard Business Review
Publisher: Harvard Business Press
Total Pages: 256
Release: 2018-03-13
Genre: Business & Economics
ISBN: 1633694291

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Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes