The one-stop-source powering Predictive Modeling success, jam-packed with ready to use insights for results, loaded with all the data you need to decide how to gain and move ahead. Based on extensive research, this lays out the thinking of the most successful Predictive Modeling knowledge experts, those who are adept at continually innovating and seeing opportunities. This is the first place to go for Predictive Modeling innovation - INCLUDED are numerous real-world Predictive Modeling blueprints, presentations and templates ready for you to access and use. Also, if you are looking for answers to one or more of these questions then THIS is the title for you: What is predictive modeling healthcare? How does predictive modeling determine credit scores? How is predictive modeling used in logistic regression? What are predictive modeling analytics? What is the best book ever written on regression modeling / predictive modeling? How do I do predictive modeling without domain expertise? What are the best books on predictive modeling? What is the difference between econometric modeling and predictive modeling? What is predictive modeling software used for? How has predictive modeling revolutionized insurance? How can predictive modeling analysis be used for urban planning applications? What are the most interesting uses of predictive modeling? In what industry branch/sector is predictive modeling extensively used? Predictive Modeling: Where can I find credit score algorithm? Predictive Modeling: How can you perform accurate feature engineering/extraction? What is predictive modeling for insurance? Which Amazon EC2 instance is recommended for doing predictive modeling competitions? How does predictive modeling work in a non-profit organization?"

The one-stop-source powering Predictive Analytics success, jam-packed with ready to use insights for success, loaded with all the data you need to decide how to gain and move ahead. An one-of-a-kind book, based on extensive research, this reveals the best practices of the most successful Predictive Analytics knowledge mavens, those who are adept at continually innovating and seeing opportunity where others do not. This is the first place to go for Predictive Analytics innovation, in today's knowledge-driven business environment, professionals face particular challenges as their purpose is to discover or develop new concepts, products, or processes; the pressure to perform is intense. This title is the entryway to a single source for innovation. BONUS: Included with the book come numerous real-world Predictive Analytics blueprints, presentations and templates ready for you to download and use. This book addresses the crucial issue of Predictive Analytics adoption by presenting the facts to move beyond general observation. The model underpinning this book has been used as a predictive decision tool, tracking thousands of innovations for over more than a decade. And...this all-encompassing analysis focuses on key areas of future Predictive Analytics growth.

The one-stop-source powering Data Modeling success, jam-packed with ready to use insights for results, loaded with all the data you need to decide how to gain and move ahead. Based on extensive research, this lays out the thinking of the most successful Data Modeling knowledge experts, those who are adept at continually innovating and seeing opportunities. This is the first place to go for Data Modeling innovation - INCLUDED are numerous real-world Data Modeling blueprints, presentations and templates ready for you to access and use. Also, if you are looking for answers to one or more of these questions then THIS is the title for you: What are the new approaches for data modeling? Data Modeling: When should we not use a relational database? How to measure lookalike-ness or sameness in data modeling? What are some easy to use data modeling/data mining tools? How does someone start learning about data modeling? Are there any good resources to help practice data-modeling in Rails? What are the recent trends in data modeling (conceptual and physical) in startups? Data Modeling: What are the best resources on data modelling principles? What are some good beginner level data modeling/analytics approaches to kick start a data science/analytics team? How can I improve my data modeling skills? Does anyone knows how to do predictive data modeling and calculation of LTV? What is the evaluation phase in data modeling? Data Modeling: What is an example of a true 1-to-1 data modeling relationship? What is the best Open Source data modeling tool for relational databases currently available? Data Modeling: What are some of the good books and online resources on learning ABM using netlogo? Is there any point in NoSQL data modeling tools since many NoSQL solutions are schema-less? Is there any (good) software for data modeling (entity relationship diagrams, UML, etc.) in 3D? What are the most ideal books to learn about advanced data modeling? ...and much more..."

The one-stop-source powering Demand Forecasting success, jam-packed with ready to use insights for results, loaded with all the data you need to decide how to gain and move ahead. Based on extensive research, this lays out the thinking of the most successful Demand Forecasting knowledge experts, those who are adept at continually innovating and seeing opportunities. This is the first place to go for Demand Forecasting innovation - INCLUDED are numerous real-world Demand Forecasting blueprints, presentations and templates ready for you to access and use. Also, if you are looking for answers to one or more of these questions then THIS is the title for you: What are the best demand forecasting models? What are the most innovative demand forecasting models? How is electricity demand forecasting done? What are the different demand forecasting techniques? What are the acceptable values for mean squared percentage error in a demand forecasting model? What variables should be considered when selecting a good model/method for demand forecasting? What are the best methods of demand forecasting? Supply Chain: Are there any examples of big data paradigm being successfully used in demand forecasting? What is demand forecasting and how can it help in business? How can demand forecasting be done in case of highly commoditized products? Can products be launched into market without demand forecasting? What are some simple tools available for demand forecasting and inventory management for a startup selling products on eCommerce sites and a few offline stores? ...and much more..."

The one-stop-source powering Data Engineering success, jam-packed with ready to use insights for success, loaded with all the data you need to decide how to gain and move ahead. An one-of-a-kind book, based on extensive research, this reveals the best practices of the most successful Data Engineering knowledge mavens, those who are adept at continually innovating and seeing opportunity where others do not. This is the first place to go for Data Engineering innovation, in today's knowledge-driven business environment, professionals face particular challenges as their purpose is to discover or develop new concepts, products, or processes; the pressure to perform is intense. This title is the entryway to a single source for innovation. BONUS: Included with the book come numerous real-world Data Engineering blueprints, presentations and templates ready for you to download and use. This book addresses the crucial issue of Data Engineering adoption by presenting the facts to move beyond general observation. The model underpinning this book has been used as a predictive decision tool, tracking thousands of innovations for over more than a decade. And...this all-encompassing analysis focuses on key areas of future Data Engineering growth.

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

The one-stop-source powering Customer Analytics success, jam-packed with ready to use insights for results, loaded with all the data you need to decide how to gain and move ahead. Based on extensive research, this lays out the thinking of the most successful Customer Analytics knowledge experts, those who are adept at continually innovating and seeing opportunities. This is the first place to go for Customer Analytics innovation - INCLUDED are numerous real-world Customer Analytics blueprints, presentations and templates ready for you to access and use. Also, if you are looking for answers to one or more of these questions then THIS is the title for you: What does customer analytics entail? Can businesses use credit card data for customer analytics? Bootstrapped Customer Analytics vs. Strategic Hiring? What customer analytics do you use to drive sales up? Can a user/customer analytics tools replace a CRM for a subscription business (SaaS)? What are the best small/medium customer analytics firms? Which type of the NOSQL database would be more efficient for recommendation engine for customer analytics domain? Data Modeling: What are some good resources (books, blogs etc.) to learn data mining / predictive modeling techniques especially focused on customer analytics? Which companies do a great job using customer analytics to generate real value? What fraction of e-commerce enterprises utilize customer analytics in their decision making? ...and much more..."