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Author: Matt Taddy
Publisher: McGraw Hill Professional
ISBN: 1260452786
Category : Business & Economics
Languages : en
Pages : 350
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Book Description
Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.
Author: Matt Taddy
Publisher: McGraw Hill Professional
ISBN: 1260452786
Category : Business & Economics
Languages : en
Pages : 350
Get Book Here
Book Description
Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.
Author: A.J. Bent
Publisher: Springer Science & Business Media
ISBN: 1475766904
Category : Technology & Engineering
Languages : en
Pages : 437
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Book Description
The popularity of the 1973 fifth edition of The Technology of Cake Making has continued in many of the English-speaking countries throughout the world. This sixth edition has been comprehensively revised and brought up to date with new chapters on Cream, butter and milkfat products, Lactose, Yeast aeration, Emulsions and emulsifiers, Water activity and Reduced sugar Eggs and egg products, Baking fats, and lower fat goods. The chapters on Sugars, Chemical aeration, Nuts in confectionery, Chocolate, Pastries, Nutritional value and Packaging have been completely rewritten. The increased need for the continuous development of new products does not of necessity mean that new technology has to be constantly introduced. Many of the good old favourites may continue to be produced for many years and they form suitable 'bench marks' for new product development. The sixth edition introduces the use of relative density to replace specific volume as a measure of the amount of aeration in a cake batter (the use of relative density is in line with international agreement). Specific volume is kept as a measurement of baked product volume since the industry is comfortable with the concept that, subject to an upper limit, an increase in specific volume coincides with improvement in cake quality.
Author: Andrew Kusiak
Publisher: John Wiley & Sons
ISBN: 9780471554929
Category : Business & Economics
Languages : en
Pages : 614
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Book Description
Presents a top-down approach to the design, development, testing and recyclability of products, components and systems across a wide range of industries. Starting with the desired result and working back through the details, it shows how to produce goods, taking into account the challenges of actual manufacture, what the reliability requirements should be, quality control, associated costs, customer needs and more. Additional features include case studies and team negotiating. Also well-illustrated with figures, photographs, charts and tables and includes an extensive bibliography.
Author: Srikanta Patnaik
Publisher: Springer Nature
ISBN: 303072929X
Category : Technology & Engineering
Languages : en
Pages : 678
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Book Description
This book offers a timely review of cutting-edge applications of computational intelligence to business management and financial analysis. It covers a wide range of intelligent and optimization techniques, reporting in detail on their application to real-world problems relating to portfolio management and demand forecasting, decision making, knowledge acquisition, and supply chain scheduling and management.
Author: Luiz Paulo Favero
Publisher: Academic Press
ISBN: 0128112174
Category : Business & Economics
Languages : en
Pages : 1246
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Book Description
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. - Combines statistics and operations research modeling to teach the principles of business analytics - Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business - Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs
Author: S. N. Murthy
Publisher: Excel Books India
ISBN: 9788174465795
Category : Business
Languages : en
Pages : 416
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Book Description
Business research methods will serve as a text book on marketing research for students pursuing courses in management and commerce. The main focus is on the Indian context. Various analytical tools used in research methods are given along with exhaustive coverage and illustrations. Assignments are included in various chapters to help in acquiring in-depth subject knowledge and application orientation. The book contains 7 sections divided into 23 chapters. Case studies are included which will help to develop analytical skills. SPSS application has been described wherever necessary. The book can be of great help to MBA, PGDBM, MMS, BBA and Commerce students.
Author: Mariette Awad
Publisher: Apress
ISBN: 1430259906
Category : Computers
Languages : en
Pages : 263
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Book Description
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.
Author: Eric Scherer
Publisher: Springer Science & Business Media
ISBN: 3642603130
Category : Business & Economics
Languages : en
Pages : 393
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Book Description
Shop floor control and namely the problem of job shop scheduling have been fields of research for a long time. However, until now no comprehensive framework on the various aspects exists. This book will provide a systems perspective towards shop floor control by stressing its sociotechnical and cybernetical nature. It focuses on the behavioral aspects of control activities and sees the shop floor as the center of value-adding manufacturing activities within an enterprise. The book enables the reader to understand the interaction of organization, information technology and human resources. This eventually allows to achieve holistic and agile solutions and facilitates profound organizational change. The book will therefore provide a welcome addition to several standard textbooks on the issue.
Author: Edward Crookshanks
Publisher: Apress
ISBN: 1484207289
Category : Computers
Languages : en
Pages : 201
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Book Description
This book provides an overview of tools and techniques used in enterprise software development, many of which are not taught in academic programs or learned on the job. This is an ideal resource containing lots of practical information and code examples that you need to master as a member of an enterprise development team. This book aggregates many of these "on the job" tools and techniques into a concise format and presents them as both discussion topics and with code examples. The reader will not only get an overview of these tools and techniques, but also several discussions concerning operational aspects of enterprise software development and how it differs from smaller development efforts. For example, in the chapter on Design Patterns and Architecture, the author describes the basics of design patterns but only highlights those that are more important in enterprise applications due to separation of duties, enterprise security, etc. The architecture discussion revolves has a similar emphasis – different teams may manage different aspects of the application’s components with little or no access to the developer. This aspect of restricted access is also mentioned in the section on logging. Theory of logging and discussions of what to log are briefly mentioned, the configuration of the logging tools is demonstrated along with a discussion of why it’s very important in an enterprise environment.
Author: Robert D. Brown III
Publisher: Apress
ISBN: 1484234952
Category : Computers
Languages : en
Pages : 287
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Book Description
This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and capital allocation decisions. Business case analysis, often conducted in spreadsheets, exposes decision makers to additional risks that arise just from the use of the spreadsheet environment. R has become one of the most widely used tools for reproducible quantitative analysis, and analysts fluent in this language are in high demand. The R language, traditionally used for statistical analysis, provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis. The main tutorial follows the case in which a chemical manufacturing company considers constructing a chemical reactor and production facility to bring a new compound to market. There are numerous uncertainties and risks involved, including the possibility that a competitor brings a similar product online. The company must determine the value of making the decision to move forward and where they might prioritize their attention to make a more informed and robust decision. While the example used is a chemical company, the analysis structure it presents can be applied to just about any business decision, from IT projects to new product development to commercial real estate. The supporting tutorials include the perspective of the founder of a professional service firm who wants to grow his business and a member of a strategic planning group in a biomedical device company who wants to know how much to budget in order to refine the quality of information about critical uncertainties that might affect the value of a chosen product development pathway. What You’ll Learn Set up a business case abstraction in an influence diagram to communicate the essence of the problem to other stakeholders Model the inherent uncertainties in the problem with Monte Carlo simulation using the R language Communicate the results graphically Draw appropriate insights from the results Develop creative decision strategies for thorough opportunity cost analysis Calculate the value of information on critical uncertainties between competing decision strategies to set the budget for deeper data analysis Construct appropriate information to satisfy the parameters for the Monte Carlo simulation when little or no empirical data are available Who This Book Is For Financial analysts, data practitioners, and risk/business professionals; also appropriate for graduate level finance, business, or data science students
