This fully illustrated step-by-step tutorial is based on proven training content that has been highly praised by hundreds of developers in product training courses given as part of the BPM Suite 11g rollout. You will learn how to build a business process application project iteratively with each chapter introducing new technology components and adding a functional increment. Each chapter comes with a working solution for your reference. You can use the solution to start the tutorial at any point or to jump around to the chapters most interesting to you. This clear and detailed tutorial is perfect for both new and experienced business process developers, process architects, and process analysts looking for a pragmatic and hands-on approach to learning Oracle BPM Suite 11g.

Combine high volume data movement, complex transformations and real-time data integration with the robust capabilities of ODI in this practical guide.

This hands-on, example-driven guide is a practical getting started tutorial with plenty of step-by-step instructions for beginner to intermediate level readers working with BPEL PM in Oracle SOA SuiteWritten for SOA developers, administrators, architects, and engineers who want to get started with Oracle BPEL PM 11g. No previous experience with BPEL PM is required, but an understanding of SOA and web services is assumed

Master Oracle Business Process Management Suite 11g Written by Oracle business process management experts, Oracle Business Process Management Suite 11g Handbook is a balanced combination of essential BPM concepts, best practices, and a detailed treatment of all the powerful features and functionalities of Oracle BPM Suite 11g. The book explains how to plan, develop, and deploy process-based business applications and enable enterprise-wide continuous process improvement. Implement successful BPM projects with help from this Oracle Press guide. Understand the architecture and functionalities of Oracle BPM Suite 11g Master BPMN 2.0 for business process modeling and implementation Address agility, business control, and transparency requirements with Oracle Business Rules 11g Develop rich interfaces with Oracle Application Development Framework (Oracle ADF) Work with the human task component of Oracle BPM 11g Plan a BPM initiative using the Oracle roadmap approach Apply the Oracle process engineering method to identify, select, define, and refine appropriate processes Implement a business process application using proven technical design and project delivery strategies

Define, model, implement, and monitor real-world BPEL business processes with SOA powered BPM for Oracle SOA Suite with this book and eBook.

This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.

This book is written in simple, easy to understand format with lots of screenshots and step-by-step explanations. If you are a BPM developer, looking to develop robust BPM solutions without impediments, then this is the best guide for you. This book assumes that you have a fundamental knowledge of BPM.