Learning Salesforce Einstein
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Learning Salesforce Einstein
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Author : Mohith Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-28
Learning Salesforce Einstein written by Mohith Shrivastava and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-28 with Computers categories.
Incorporate the power of Einstein in your Salesforce application About This Book Make better predictions of your business processes using prediction and predictive modeling Build your own custom models by leveraging PredictionIO on the Heroku platform Integrate Einstein into various cloud services to predict sales, marketing leads, insights into news feeds, and more Who This Book Is For This book is for developers, data scientists, and Salesforce-experienced consultants who want to explore Salesforce Einstein and its current offerings. It assumes some prior experience with the Salesforce platform. What You Will Learn Get introduced to AI and its role in CRM and cloud applications Understand how Einstein works for the sales, service, marketing, community, and commerce clouds Gain a deep understanding of how to use Einstein for the analytics cloud Build predictive apps on Heroku using PredictionIO, and work with Einstein Predictive Vision Services Incorporate Einstein in the IoT cloud Test the accuracy of Einstein through Salesforce reporting and Wave analytics In Detail Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the force.com platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce's various cloud offerings and how they can use Einstein's capabilities and enhance applications. Style and approach This book takes a straightforward approach to explain Salesforce Einstein and all of its potential applications. Filled with examples, the book presents the facts along with seasoned advice and real-world use cases to ensure you have all the resources you need to incorporate the power of Einstein in your work.
Learning Salesforce Lightning Application Development
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Author : Mohith Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-31
Learning Salesforce Lightning Application Development written by Mohith Shrivastava and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Computers categories.
Build, design, and style beautiful and informative applications on the Salesforce Lightning platform Key Features Build and Test Lightning Components that enhance application usability and adaptability Apply Security Best Practices to your Custom Lightning Components Design Lightning Components for Salesforce UIs such as Lightning Pages, Salesforce 1 Application, Communities, and more. Book Description Built on the Salesforce App Cloud, the new Salesforce Lightning Experience combines three major components: Lightning Design System, Lightning App Builder, and Lightning Components, to provide an enhanced user experience. This book will enable you to quickly create modern, enterprise apps with Lightning Component Framework. You will start by building simple Lightning Components and understanding the Lightning Components architecture. The chapters cover the basics of Lightning Component Framework semantics and syntax, the security features provided by Locker Service, and use of third-party libraries inside Lightning Components. The later chapters focus on debugging, performance tuning, testing using Lightning Testing Services, and how to publish Lightning Components on Salesforce AppExchange. What you will learn Understand Lightning Components architecture Learn Locker security best practices Debug and Improve performance of your Lightning Components Use third-party libraries along with Lightning Component Framework Learn how to publish Lightning Components on AppExchange Use Lightning Out to take your Lightning Components outside the Salesforce platform Who this book is for This book is for Salesforce developers or developers from other platforms who are familiar with HTML, CSS, and JavaScript and want to build and test Salesforce Lightning components. No knowledge of Salesforce Lightning is required.
Getting Started With Salesforce Einstein Analytics
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Author : Johan Yu
language : en
Publisher: Apress
Release Date : 2019-09-11
Getting Started With Salesforce Einstein Analytics written by Johan Yu and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-11 with Computers categories.
Build interactive dashboards using Salesforce Einstein analytics. Explore all of your data quickly and easily by providing AI-powered advanced analytics, right in Salesforce. You will manage datasets, query data with Salesforce Analytics Query Language (SAQL), and customize dashboards. Because Einstein Analytics is new, the curve to learn this technology can be difficult. This book guides you step-by-step in simple, easy-to-understand terms to get data from the Salesforce platform to the Einstein Analytics platform and also shows you how to import external data (e.g., CSV files). Core chapters focus on understanding data sources, dataflow, dataset, and lens leading up to building dashboards from scratch. Advanced features such as data transformation using computeExpression and computeRelative as well as dataflow with a multi-value lookup are explored. What You Will Learn Use data from Salesforce and external sources Create a dataflow to build a flexible dataset Build dashboards using Einstein Analytics Explore and analyze data using Einstein Analytics Utilize SAQL and binding to create advance dashboards Who This Book Is For IT users getting started with Einstein Analytics, Salesforce consultants starting new Einstein Analytics projects, and power users familiar with Salesforce reporting and dashboards who want to get up to speed on new analytics features
Learning Tableau 2022
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Author : Joshua N. Milligan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-08-26
Learning Tableau 2022 written by Joshua N. Milligan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-26 with Computers categories.
Now in color, this edition of Learning Tableau will empower you to bring data to life and make better business decisions. Purchase of the print or Kindle book includes a free eBook in PDF format. Key FeaturesLearn the basics of data analysis, from snappy visualizations to comprehensive dashboardsGain meaningful insights with geospatial analysis, scripting extensions, and other advanced methodsExplore the latest Tableau 2022 features, including Einstein Discovery and Explain DataBook Description Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau's latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You'll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources with Tableau's Data Model capabilities, along with maps and geospatial visualization. You will further use Tableau Prep Builder's ability to efficiently clean and structure data. By the end of this book, you will be proficient in implementing the powerful features of Tableau 2022 to improve the business intelligence insights you can extract from your data. What you will learnDevelop stunning visualizations to explain complex data with clarityBuild interactive dashboards to drive actionable user insightsExplore Data Model capabilities and interlink data from various sourcesCreate and use calculations to solve problems and enrich your analyticsEnable smart decision-making with data clustering, distribution, and forecastingExtend Tableau's native functionality with extensions, scripts, and AI through CRM Analytics (formerly Einstein Analytics)Leverage Tableau Prep Builder's amazing capabilities for data cleaning and structuringShare your data stories to build a culture of trust and actionWho this book is for This Tableau book is for aspiring BI developers and data analysts, data scientists, researchers, and anyone else who wants to gain a deeper understanding of data through Tableau. This book starts from the ground up, so you won't need any prior experience with Tableau before you dive in, but a full Tableau license (or 14-day demo license) is essential to be able to make use of all the exercises.
Salesforce For Beginners
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Author : Sharif Shaalan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-05-29
Salesforce For Beginners written by Sharif Shaalan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-29 with Computers categories.
Get a 360-degree view of the Salesforce platform and learn how to use it for sales, service, marketing, and automating business processes. Key FeaturesUnderstand how to use core Salesforce objects for maximum efficiencyBuild various dashboards and reports to analyze results and improve visibility in your business processesLearn the basics of Salesforce administration and mobile app set upBook Description Salesforce is the world's leading Customer Relationship Management (CRM) software, helping businesses connect with their constituents and partners. This book will give you a comprehensive introduction to managing sales, marketing, customer relationships, and overall administration for your organization. You'll learn how to configure and use Salesforce for maximum efficiency and return on investment. You'll start by learning how to create activities, manage leads, and develop your prospects and sales pipeline using opportunities and accounts, and then understand how you can enhance marketing activities using campaigns. Packed with real-world business use cases, this Salesforce book will show you how to analyze your business information accurately to make productive decisions. As you advance, you'll get to grips with building various reports and dashboards in Salesforce to derive valuable business insights. Finally, you'll explore tools such as process builder, approval processes, and assignment rules to achieve business process automation and set out on the path to becoming a successful Salesforce Administrator. By the end of the book, you'll have learned how to use Salesforce effectively to achieve your business goals. What you will learnUnderstand the difference between Salesforce Lightning and Salesforce ClassicCreate and manage leads in SalesforceExplore business development with accounts and contacts in SalesforceFind out how stages and sales processes help you manage your opportunity pipelineAchieve marketing goals using Salesforce campaignsPerform business analysis using reports and dashboardsGain a high-level overview of the items in the administration sectionGrasp the different aspects needed to build an effective and flexible Salesforce security modelWho this book is for If you're new to Salesforce and want to learn it from scratch, this book is for you. No prior knowledge of Salesforce is required to get started with this book.
Learning Einstein Analytics
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Author : santosh chitalkar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-29
Learning Einstein Analytics written by santosh chitalkar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-29 with Computers categories.
Learn to confidently setup and create app, lenses, dashboards using Salesforce Einstein Analytics. Key Features Explore Einstein analytics on desktop as well as mobile platforms Turn data into smarter sales with Einstein Analytics for Sales Visualize your data with preloaded as well as customized dashboards Book Description Salesforce Einstein analytics aka Wave Analytics is a cloud-based platform which connects data from the multiple sources and explores it to uncover insights. It empowers sales reps, marketers, and analysts with the insights to make customer interactions smarter, without building mathematical models. You will learn to create app, lenses, dashboards and share dashboards with other users. This book starts off with explaining you fundamental concepts like lenses, step, measures and sets you up with Einstein Analytics platform. We then move on to creating an app and here you will learn to create datasets, dashboards and different ways to import data into Analytics. Moving on we look at Einstein for sales, services, and marketing individually. Here you will learn to manage your pipeline, understand important business drivers and visualize trends. You will also learn features related to data monitoring tools and embedding dashboards with lightning, visualforce page and mobile devices. Further, you will learn advanced features pertaining to recent advancements in Einstein which include machine learning constructs and getting predictions for events. By the end of this book, you will become proficient in the Einstein analytics, getting insights faster and understanding your customer in a better way. What you will learn Create app, lenses, and dashboards using Einstein. Visualize data utilizing all the widgets available with Einstein. Understand Einstein for Sales, Service, and Marketing separately. Use Data monitoring tools to monitor data flow and system jobs. Abstract machine learning constructs and make predictions on events Who this book is for This book is for data scientists, business users, developers who want to explore business data using the Salesforce Einstein Analytics. Knowledge of the Salesforce platform is required.
A Friendly Guide To Data Science
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Author : Kelly P. Vincent
language : en
Publisher: Springer Nature
Release Date : 2025-06-26
A Friendly Guide To Data Science written by Kelly P. Vincent and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-26 with Computers categories.
Unlock the world of data science—no coding required. Curious about data science but not sure where to start? This book is a beginner-friendly guide to what data science is and how people use it. It walks you through the essential topics—what data analysis involves, which skills are useful, and how terms like “data analytics” and “machine learning” connect—without getting too technical too fast. Data science isn’t just about crunching numbers, pulling data from a database, or running fancy algorithms. It’s about asking the right questions, understanding the process from start to finish, and knowing what’s possible (and what’s not). This book teaches you all of that, while also introducing important topics like ethics, privacy, and security—because working with data means thinking about people, too. Whether you're a student exploring new skills, a professional navigating data-driven decisions, or someone considering a career change, this book is your friendly gateway into the world of data science, one of today’s most exciting fields. No coding or programming experience? No problem. You'll build a solid foundation and gain the confidence to engage with data science concepts— just as AI and data become increasingly central to everyday life. What You Will Learn Grasp foundational statistics and how it matters in data analysis and data science Understand the data science project life cycle and how to manage a data science project Examine the ethics of working with data and its use in data analysis and data science Understand the foundations of data security and privacy Collect, store, prepare, visualize, and present data Identify the many types of machine learning and know how to gauge performance Prepare for and find a career in data science Who This Book is for A wide range of readers who are curious about data science and eager to build a strong foundation. Perfect for undergraduates in the early semesters of their data science degrees, as it assumes no prior programming or industry experience. Professionals will find particular value in the real-world insights shared through practitioner interviews. Business leaders can use it to better understand what data science can do for them and how their teams are applying it. And for career changers, this book offers a welcoming entry point into the field—helping them explore the landscape before committing to more intensive learning paths like degrees or boot camps.
Designing Deep Learning Systems
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Author : Chi Wang
language : en
Publisher: Simon and Schuster
Release Date : 2023-09-19
Designing Deep Learning Systems written by Chi Wang and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-19 with Computers categories.
A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning’s design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer. About the technology To be practically usable, a deep learning model must be built into a software platform. As a software engineer, you need a deep understanding of deep learning to create such a system. Th is book gives you that depth. About the book Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer’s perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you’ll need to build your own maintainable, efficient, and scalable deep learning platforms. What's inside The deep learning development cycle Automate training in TensorFlow and PyTorch Dataset management, model serving, and hyperparameter tuning A hands-on deep learning lab About the reader For software developers and engineering-minded data scientists. Examples in Java and Python. About the author Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. Table of Contents 1 An introduction to deep learning systems 2 Dataset management service 3 Model training service 4 Distributed training 5 Hyperparameter optimization service 6 Model serving design 7 Model serving in practice 8 Metadata and artifact store 9 Workflow orchestration 10 Path to production
Artificial Intelligence In Practice
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Author : Bernard Marr
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-15
Artificial Intelligence In Practice written by Bernard Marr and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-15 with Comics & Graphic Novels categories.
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
Automated Machine Learning For Business
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Author : Kai R. Larsen
language : en
Publisher: Oxford University Press
Release Date : 2021
Automated Machine Learning For Business written by Kai R. Larsen and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Business & Economics categories.
Teaches the machine learning process for business students and professionals using automated machine learning, a new development in data science that requires only a few weeks to learn instead of years of training Though the concept of computers learning to solve a problem may still conjure thoughts of futuristic artificial intelligence, the reality is that machine learning algorithms now exist within most major software, including Websites and even word processors. These algorithms are transforming society in the most radical way since the Industrial Revolution, primarily through automating tasks such as deciding which users to advertise to, which machines are likely to break down, and which stock to buy and sell. While this work no longer always requires advanced technical expertise, it is crucial that practitioners and students alike understand the world of machine learning. In this book, Kai R. Larsen and Daniel S. Becker teach the machine learning process using a new development in data science: automated machine learning (AutoML). AutoML, when implemented properly, makes machine learning accessible by removing the need for years of experience in the most arcane aspects of data science, such as math, statistics, and computer science. Larsen and Becker demonstrate how anyone trained in the use of AutoML can use it to test their ideas and support the quality of those ideas during presentations to management and stakeholder groups. Because the requisite investment is a few weeks rather than a few years of training, these tools will likely become a core component of undergraduate and graduate programs alike. With first-hand examples from the industry-leading DataRobot platform, Automated Machine Learning for Business provides a clear overview of the process and engages with essential tools for the future of data science.