Best Predictive Analytics Books & Best Predictive Analytics Courses in 2021

Best Predictive Analytics Books 2021

Best Predictive Analytics Courses 2021


Best Predictive Analytics Tutorials 2021

Introduction to Predictive Analytics on SAP HANA

This entry-to-intermediate SAP HANA Predictive Analytics course will help you master many techniques important to begin building sophisticated predictive analytics applications that use the power of SAP HANA and Business Intelligence. The course is designed so that you can master all the techniques gradually, starting with basic and relatively simple techniques before moving on to the more demanding techniques that Business Intelligence professionals use to build predictive analytics applications for their clients. The course will take you step-by-step through the process of creating the required HANA objects, such as tables, views, and predictive analytics SQL scripts. In particular, from this course you will learn:

Fundamentals of the predictive analysis library,
The structures involved, such as HANA tables, views, PAL SQL procedures and more,
A comparison of the raw PAL SQL code with the HANA analytical processes available in SAP BW by creating the comparable HANA AP in BW,
Integration of predictive analytics in SAP BW and SAP Lumira


This course does not assume any knowledge of the HANA predictive analytics library. BW and HANA experience would be helpful.

What this course is not:

This course does not cover all predictive analytics algorithms. It covers enough algorithms so that you can familiarize yourself with their use and apply the techniques to any other function. Covering all algorithms will result in a high level of repetition with no real value. What sets this course apart from anything available on other platforms is the fact that it covers the integration and application of the Predictive Analytics library with the various other visualization and viewing platforms.

SAP Big Data Predictive Analytics : An Overview

Big data analysis involves examining large sets of data to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful business information. Analytical results can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over competing organizations, and other business advantages.

The main goal of big data analytics is to help businesses make more informed business decisions by enabling predictive data modeling specialists and other analytics professionals to analyze large volumes of data. transaction, as well as other forms of data that may be left untapped by conventional business intelligence programs. This could include web server logs and internet feed data, social media content and social media activity reports, text of customer emails and survey responses, detailed phone call records. mobile and machine data captured by sensors connected to the Internet of Things.

Big data can be analyzed with software tools commonly used in advanced analytical disciplines such as predictive analytics, data mining, text analysis, and statistical analysis. Potential pitfalls that can trip organizations into big data analytics initiatives include a lack of internal analytics skills and the high cost of hiring experienced analytics professionals. The amount of information typically involved and its variety can also cause data management headaches, including issues with data quality and consistency. Additionally, integrating Hadoop systems and data warehouses can be a challenge, although various vendors now offer software connectors between Hadoop and relational databases, as well as other data integration tools with Big Data capabilities. SAP has a comprehensive suite of solutions to support the entire analytical scope.

Python Data Products for Predictive Analytics Specialization

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego.

This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills.

Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets.

Best Predictive Analytics Books 2021

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
  • In this rich, fascinating - surprisingly accessible - introduction, leading expert Eric Siegel...
  • Siegel, Eric (Author)
  • English (Publication Language)
  • 368 Pages - 01/20/2016 (Publication Date) - Wiley (Publisher)

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel. An introduction for everyone. In this rich, fascinating and surprisingly accessible manual, eminent expert Eric Siegel reveals how predictive analytics (also known as machine learning) works and how it affects everyone on a daily basis. Rather than a “how-to” for tech experts, the book serves both lay readers and experts by covering new case studies and the latest cutting edge techniques.

Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies

Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked...
  • Hardcover Book
  • Kelleher, John D. (Author)
  • English (Publication Language)
  • 856 Pages - 10/20/2020 (Publication Date) - The MIT Press (Publisher)

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.

The book is accessible, offering nontechnical explanations of the ideas underpinning each approach before introducing mathematical models and algorithms. It is focused and deep, providing students with detailed knowledge on core concepts, giving them a solid basis for exploring the field on their own. Both early chapters and later case studies illustrate how the process of learning predictive models fits into the broader business context. The two case studies describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book can be used as a textbook at the introductory level or as a reference for professionals.

Predictive Analytics for Human Resources

Predictive Analytics for Human Resources (Wiley and SAS Business Series)
  • Hardcover Book
  • Fitz-enz, Jac (Author)
  • English (Publication Language)
  • 176 Pages - 07/18/2014 (Publication Date) - Wiley (Publisher)

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 HR Analytics, Text Mining & Organizational Network Analysis with Excel

SaleBestseller No. 1
Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst
  • John Wiley Sons
  • Abbott, Dean (Author)
  • English (Publication Language)
  • 464 Pages - 04/04/2014 (Publication Date) - Wiley (Publisher)
Bestseller No. 2
Data Science and Predictive Analytics: Biomedical and Health Applications using R
  • Amazon Kindle Edition
  • Ivo D. Dinov (Author)
  • English (Publication Language)
  • 1157 Pages - 08/27/2018 (Publication Date) - Springer (Publisher)
SaleBestseller No. 3
Predictive Analytics For Dummies
  • Bari, Anasse (Author)
  • English (Publication Language)
  • 464 Pages - 10/31/2016 (Publication Date) - For Dummies (Publisher)
Bestseller No. 4
Predictive HR Analytics: Mastering the HR Metric
  • Edwards, Dr Martin (Author)
  • English (Publication Language)
  • 536 Pages - 03/28/2019 (Publication Date) - Kogan Page (Publisher)
SaleBestseller No. 5
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
  • In this rich, fascinating - surprisingly accessible - introduction, leading expert Eric Siegel...
  • Siegel, Eric (Author)
  • English (Publication Language)
  • 368 Pages - 01/20/2016 (Publication Date) - Wiley (Publisher)
Bestseller No. 6
Modeling Techniques In Predictive Analytics With Python And R: A Guide To Data Science
  • Thomas W. Miller (Author)
  • English (Publication Language)
  • 08/03/2021 (Publication Date) - Pearson Education (Publisher)
SaleBestseller No. 7
Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner
  • Kotu, Vijay (Author)
  • English (Publication Language)
  • 448 Pages - 12/17/2014 (Publication Date) - Morgan Kaufmann (Publisher)
SaleBestseller No. 8
Fundamentals of Predictive Analytics with JMP, Second Edition
  • Klimberg PhD, Ron (Author)
  • English (Publication Language)
  • 406 Pages - 12/15/2016 (Publication Date) - SAS Institute (Publisher)
Bestseller No. 9
Applying Predictive Analytics
  • Hardcover Book
  • McCarthy (Author)
  • English (Publication Language)
  • 216 Pages - 03/21/2019 (Publication Date) - Springer (Publisher)
Bestseller No. 10
SAP Predictive Analytics: The Comprehensive Guide (SAP PRESS) (Rheinwerk Publishing)
  • Hardcover Book
  • Antoine Chabert (Author)
  • English (Publication Language)
  • 491 Pages - 12/27/2017 (Publication Date) - SAP Press (Publisher)
Bestseller No. 11
Predictive HR Analytics
  • Ng, Mong Shen (Author)
  • English (Publication Language)
  • 424 Pages - 11/27/2018 (Publication Date) - Independently published (Publisher)
SaleBestseller No. 12
Practical Predictive Analytics and Decisioning Systems for Medicine: Informatics Accuracy and...
  • Miner, Gary (Author)
  • English (Publication Language)
  • 1110 Pages - 09/02/2016 (Publication Date) - Academic Press (Publisher)
SaleBestseller No. 13
Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
  • Hardcover Book
  • Larose, Daniel T. (Author)
  • English (Publication Language)
  • 824 Pages - 03/16/2015 (Publication Date) - Wiley (Publisher)
Bestseller No. 14
Mastering Predictive Analytics with R - Second Edition: Machine learning techniques for advanced...
  • Miller, James D. (Author)
  • English (Publication Language)
  • 448 Pages - 08/18/2017 (Publication Date) - Packt Publishing (Publisher)
SaleBestseller No. 15
Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data...
  • Hardcover Book
  • Baesens, Bart (Author)
  • English (Publication Language)
  • 400 Pages - 08/17/2015 (Publication Date) - Wiley (Publisher)
Bestseller No. 16
Mastering Predictive Analytics with R
  • Forte, Rui Miguel (Author)
  • English (Publication Language)
  • 414 Pages - 06/17/2015 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 17
Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics
  • Andrew Greasley (Author)
  • English (Publication Language)
  • 250 Pages - 10/21/2019 (Publication Date) - De|G PRESS (Publisher)
SaleBestseller No. 18
Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods (Business in the...
  • Finlay, S. (Author)
  • English (Publication Language)
  • 272 Pages - 01/01/2014 (Publication Date) - Palgrave Macmillan (Publisher)
Bestseller No. 19
Fantasy Football Predictive Analytics: Using Analytics to Solve the 2021 Fantasy Football Season
  • Amazon Kindle Edition
  • Tefertiller, Rhys (Author)
  • English (Publication Language)
  • 115 Pages - 07/25/2021 (Publication Date)
Bestseller No. 20
Hands-On Predictive Analytics with Python: Master the complete predictive analytics process, from...
  • Amazon Kindle Edition
  • Fuentes, Alvaro (Author)
  • English (Publication Language)
  • 332 Pages - 12/28/2018 (Publication Date) - Packt Publishing (Publisher)