Monetizing Machine Learning

Author : Manuel Amunategui,Mehdi Roopaei
Publisher : Apress
Page : 510 pages
File Size : 53,7 Mb
Release : 2018-09-12
Category : Computers
ISBN : 9781484238738

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Monetizing Machine Learning by Manuel Amunategui,Mehdi Roopaei Pdf

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time. Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book. What You’ll Learn Extend your machine learning models using simple techniques to create compelling and interactive web dashboards Leverage the Flask web framework for rapid prototyping of your Python models and ideasCreate dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more Harness the power of TensorFlow by exporting saved models into web applications Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored contentCreate dashboards with paywalls to offer subscription-based accessAccess API data such as Google Maps, OpenWeather, etc.Apply different approaches to make sense of text data and return customized intelligence Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back Utilize the freemium offerings of Google Analytics and analyze the results Take your ideas all the way to your customer's plate using the top serverless cloud providers Who This Book Is For Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.

Author : Puneet Mathur
Publisher : Apress
Page : 384 pages
File Size : 46,7 Mb
Release : 2018-12-12
Category : Computers
ISBN : 9781484237878

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Machine Learning Applications Using Python by Puneet Mathur Pdf

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you’ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You’ll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will LearnDiscover applied machine learning processes and principles Implement machine learning in areas of healthcare, finance, and retail Avoid the pitfalls of implementing applied machine learning Build Python machine learning examples in the three subject areas Who This Book Is For Data scientists and machine learning professionals.

Author : Andrew Roman Wells,Kathy Williams Chiang
Publisher : John Wiley & Sons
Page : 371 pages
File Size : 55,7 Mb
Release : 2017-03-13
Category : Business & Economics
ISBN : 9781119356240

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Monetizing Your Data by Andrew Roman Wells,Kathy Williams Chiang Pdf

Transforming data into revenue generating strategies and actions Organizations are swamped with data—collected from web traffic, point of sale systems, enterprise resource planning systems, and more, but what to do with it? Monetizing your Data provides a framework and path for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics. There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns. The companion website, www.monetizingyourdata.com, provides templates, checklists, and examples to help you apply the methodology in your environment, and the expert author team provides authoritative guidance every step of the way. This book shows you how to use your data to: Monetize your data to drive revenue and cut costs Connect your data to decisions that drive action and deliver value Develop analytic tools to guide managers up and down the ladder to better decisions Turning data into action is key; data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; Monetizing your Data walks you through the translation and transformation to help you leverage your data into value creating strategies.

Author : Waheed Khan
Publisher : Waheed Khan
Page : 81 pages
File Size : 51,7 Mb
Release : 2024-06-10
Category : Computers
ISBN : 9798871618134

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The Business of AI: Monetizing, Marketing and Selling AI Products by Waheed Khan Pdf

Unlock the Moneymaking Potential of AI for Your Business (The Business of AI) Artificial intelligence already drives billions in economic value, but most businesses have yet to tap its lucrative potential. This definitive guide reveals insider strategies used by AI industry practitioners to successfully ideate, develop, market and monetize AI products across any industry to gain competitive advantages and dominate your niche. Learn high-impact business frameworks around: Validating and conceptualizing profitable AI product ideas based on market gap analysis Assembling AI development teams leveraging the right talent and technology stacks Architecting reliable and scalable machine learning operations (MLOps) Securing funding for AI startups via optimal fundraising approaches Building trust and adoption via differentiated marketing highlighting transparency Generating sales tailoring B2B and B2C monetization models around AI Ethics considerations around reducing algorithmic bias and ensuring fairness Global expansion tactics and localization techniques as you scale internationally Additionally, get exclusive insights from AI thought leaders on emerging technologies, long horizon predictions, sample case studies and more. Plus helpful appendices featuring an AI entrepreneur's resource directory across data resources, tools, cloud platforms, research groups and communities. This indispensable handbook provides pragmatic guidance for CEOs, founders, developers, marketers, sales leaders keen to capitalize on AI’s business potential and compound competitive differentiation. Buy now to future proof your firm!

Author : Valliappa Lakshmanan,Sara Robinson,Michael Munn
Publisher : O'Reilly Media
Page : 408 pages
File Size : 40,7 Mb
Release : 2020-10-15
Category : Computers
ISBN : 9781098115753

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Machine Learning Design Patterns by Valliappa Lakshmanan,Sara Robinson,Michael Munn Pdf

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly

Author : Andrew Roman Wells,Kathy Williams Chiang
Publisher : John Wiley & Sons
Page : 311 pages
File Size : 54,7 Mb
Release : 2017-02-27
Category : Business & Economics
ISBN : 9781119356257

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Monetizing Your Data by Andrew Roman Wells,Kathy Williams Chiang Pdf

Transforming data into revenue generating strategies and actions Organizations are swamped with data—collected from web traffic, point of sale systems, enterprise resource planning systems, and more, but what to do with it? Monetizing your Data provides a framework and path for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics. There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns. The companion website, www.monetizingyourdata.com, provides templates, checklists, and examples to help you apply the methodology in your environment, and the expert author team provides authoritative guidance every step of the way. This book shows you how to use your data to: Monetize your data to drive revenue and cut costs Connect your data to decisions that drive action and deliver value Develop analytic tools to guide managers up and down the ladder to better decisions Turning data into action is key; data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; Monetizing your Data walks you through the translation and transformation to help you leverage your data into value creating strategies.

Author : Hunter C Johnson
Publisher : Unknown
Page : 0 pages
File Size : 47,9 Mb
Release : 2023-07-21
Category : Electronic
ISBN : 1778900364

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Writing Books and Making Money with ChatGPT by Hunter C Johnson Pdf

The ultimate guide to writing books, get your AI money! Use ChatGPT for content creation and AI writing today! Discover the world of monetizing AI through book writing with Writing Books and Making Money with ChatGPT. Unleash the power of ChatGPT for profitable writing, explore fiction and non-fiction paths, learn step-by-step content generation, master self-publishing, monetize your AI-generated books, and scale up your AI book empire. Navigate ethical considerations and glimpse into the future of AI writing. Embrace the limitless possibilities and seize the opportunity for financial success.

Author : Mark Wickham
Publisher : Apress
Page : 410 pages
File Size : 54,8 Mb
Release : 2018-10-23
Category : Computers
ISBN : 9781484239513

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Practical Java Machine Learning by Mark Wickham Pdf

Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services. Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualization for Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data. After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java. What You Will LearnIdentify, organize, and architect the data required for ML projects Deploy ML solutions in conjunction with cloud providers such as Google and Amazon Determine which algorithm is the most appropriate for a specific ML problem Implement Java ML solutions on Android mobile devices Create Java ML solutions to work with sensor data Build Java streaming based solutionsWho This Book Is For Experienced Java developers who have not implemented machine learning techniques before.

Author : Clarence Chio,David Freeman
Publisher : "O'Reilly Media, Inc."
Page : 385 pages
File Size : 50,6 Mb
Release : 2018-01-26
Category : Computers
ISBN : 9781491979877

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Machine Learning and Security by Clarence Chio,David Freeman Pdf

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself! With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

Author : Madhavan Ramanujam,Georg Tacke
Publisher : John Wiley & Sons
Page : 263 pages
File Size : 49,6 Mb
Release : 2016-05-02
Category : Business & Economics
ISBN : 9781119240860

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Monetizing Innovation by Madhavan Ramanujam,Georg Tacke Pdf

Surprising rules for successful monetization Innovation is the most important driver of growth. Today, more than ever, companies need to innovate to survive. But successful innovation—measured in dollars and cents—is a very hard target to hit. Companies obsess over being creative and innovative and spend significant time and expense in designing and building products, yet struggle to monetize them: 72% of innovations fail to meet their financial targets—or fail entirely. Many companies have come to accept that a high failure rate, and the billions of dollars lost annually, is just the cost of doing business. Monetizing Innovations argues that this is tragic, wasteful, and wrong. Radically improving the odds that your innovation will succeed is just a matter of removing the guesswork. That happens when you put customer demand and willingness to pay in the driver seat—when you design the product around the price. It’s a new paradigm, and that opens the door to true game change: You can stop hoping to monetize, and start knowing that you will. The authors at Simon Kucher know what they’re talking about. As the world’s premier pricing and monetization consulting services company, with 800 professionals in 30 cities around the globe, they have helped clients ranging from massive pharmaceuticals to fast-growing startups find success. In Monetizing Innovation, they distil the lessons of thirty years and over 10,000 projects into a practical, nine-step approach. Whether you are a CEO, executive leadership, or part of the team responsible for innovation and new product development, this book is for you, with special sections and checklist-driven summaries to make monetizing innovation part of your company’s DNA. Illustrative case studies show how some of the world’s best innovative companies like LinkedIn, Uber, Porsche, Optimizely, Draeger, Swarovski and big pharmaceutical companies have used principles outlined in this book. A direct challenge to the status quo “spray and pray” style of innovation, Monetizing Innovation presents a practical approach that can be adopted by any organization, in any industry. Most monetizing innovation failure point home. Now more than ever, companies must rethink the practices that have lost countless billions of dollars. Monetizing Innovation presents a new way forward, and a clear promise: Go from hope to certainty.

Author : Prashant Kikani
Publisher : BPB Publications
Page : 170 pages
File Size : 45,6 Mb
Release : 2021-01-05
Category : Computers
ISBN : 9789389898705

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Demystifying Artificial intelligence by Prashant Kikani Pdf

Learn AI & Machine Learning from the first principles. KEY FEATURESÊÊ _ Explore how different industries are using AI and ML for diverse use-cases. _ Learn core concepts of Data Science, Machine Learning, Deep Learning and NLP in an easy and intuitive manner. _ Cutting-edge coverage on use of ML for business products and services. _ Explore how different companies are monetizing AI and ML technologies. _ Learn how you can start your own journey in the AI field from scratch. DESCRIPTION AI and machine learning (ML) are probably the most fascinating technologies of the 21st century. AI is literally in every industry now. From medical to climate change, education to sport, finance to entertainment, AI is disrupting every industry as we know. So, the basic knowledge of AI/ML becomes mandatory for everyone. This book is your first step to start the journey in this field. Along with basic concepts of fields, like machine learning, deep learning and NLP, we will also explore how big companies are using these technologies to deliver greater user experience and earning millions of dollars in profit. Also, we will see how the owners of small- or medium-sized businesses can leverage and integrate these technologies with their products and services. Leveraging AI and ML can become that competitive moat which can differentiate the product from others. In this book, you will learn the root concepts of AI/ML and how these inanimate machines can actually become smarter than the humans at a few tasks, and how companies are using AI and how you can leverage AI to earn profits. WHAT YOU WILL LEARN Ê _ Core concepts of data science, machine learning, deep learning and NLP in simple and intuitive words. _ How you can leverage and integrate AI technologies in your business to differentiate your product in the market. _ The limitations of traditional non-tech businesses and how AI can bridge those gaps to increase revenues and decrease costs. _ How AI can help companies in launching new products, improving existing ones and automating mundane processes. _ Explore how big tech companies are using AI to automate different tasks and providing unique product experiences to their users. WHO THIS BOOK IS FORÊÊ This book is for anyone who is curious about this fascinating technology and how it really works at its core. It is also beneficial to those who want to start their career in AI/ ML. TABLE OF CONTENTSÊ 1. Introduction 2. Going deeper in ML concepts 3. Business perspective of AI 4. How to get started and pitfalls to avoid

Author : Carlos Perez
Publisher : Lulu.com
Page : 352 pages
File Size : 41,7 Mb
Release : 2017
Category : Electronic
ISBN : 9781365879234

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The Deep Learning AI Playbook by Carlos Perez Pdf

Author : Stephan Liozu,Wolfgang Ulaga
Publisher : Ulaga & Associés
Page : 259 pages
File Size : 41,7 Mb
Release : 2018-10-30
Category : Business & Economics
ISBN : 9781945815058

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Monetizing Data by Stephan Liozu,Wolfgang Ulaga Pdf

The Digital revolution promises trillions of dollars in created value by 2030. Consultants and researchers are projecting massive and disruptive disruption in entire industrial sectors. As a results, PwC reports in their DigitalIQ report that 73% of executives say that they are investing in internet of things (IoT) and 54% in artificial intelligence. So we are experiencing a deluge of digital investments, programs, and large-scale transformations. Despite this tsunami of activities, many IoT Initiatives stall in the Proof of Concept phase and few are already considered a success. Recently, Siemens revealed that less than a fifth (18%) of surveyed companies analyze more than 60% of production data they collect. In a similar vein, Simon-Kucher & Partners (SKP) reports that 3 out of 4 firms that invested in digitalization in the past 3 years fail in their efforts due to the lack of monetization strategies, the focus on the wrong priorities, the lack of customer intimacy, and the neglect of digital pricing best practices. In fact, only 18% of these firms are true digital heroes. Despite the high level of interest and investments, the reality is that most companies are just getting started. The digital champions are not yet reaping the fruit of their investments. Most companies tend to struggle with the process of designing digital business models, with the development of truly differentiated offers, and with the monetization and pricing of their data-based offers. This book focuses on the topics of data monetization and of the value-based pricing of data-driven offers. The authors introduces a newly-developed practical data monetization roadmap that can be used by digital project teams, incubators, and digital factories to better frame their offers and to apply the principles of value-based pricing. They present options in digital pricing models and practical guidelines on how to deploy them. Readers will learn: The various monetization and value creation models for data-enabled offers The 8 steps of the data monetization framework The best practices in designing differentiated data-enabled offers The value-based pricing of data and options in digital pricing models Business model implications of switching from ownership to consumption model

Author : Francisco J. Martínez-López,Yangchun Li,Susan M. Young
Publisher : Springer Nature
Page : 242 pages
File Size : 51,6 Mb
Release : 2022-09-23
Category : Business & Economics
ISBN : 9783031145759

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Social Media Monetization by Francisco J. Martínez-López,Yangchun Li,Susan M. Young Pdf

Social media initiatives, when effectively used and correctly monetized, can engage customers better and provide higher ROI rates than traditional marketing and sales initiatives. This book presents a selection of monetization strategies that can help companies benefit from social media initiatives and overcome the current challenges in connection with generating and growing revenues. Using cases and examples covering several social media platforms, the authors describe a variety of strategies and holistic solutions for companies. In addition, the book highlights the latest social media innovations, best business practices, successful monetization cases, and strategic trends in future social media monetization. Top executives need to read this book to have a big picture of corporate-wide “social strategy,” form a “social mindset,” and infuse a “social gene” into their company’s culture, strategy, and business processes. Armed with these social elements, companies can gain confidence, effectively introduce social media tools, and invest in major social media initiatives. Due to changing consumer behavior, social media is also ideal for building and sustaining quality relationships with customers – which is why it is becoming an indispensable element in today’s business.

Author : Clarence Chio,David Freeman
Publisher : "O'Reilly Media, Inc."
Page : 386 pages
File Size : 46,5 Mb
Release : 2018-01-26
Category : Computers
ISBN : 9781491979853

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Machine Learning and Security by Clarence Chio,David Freeman Pdf

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself! With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions