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Monetizing Machine Learning

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Monetizing Machine Learning

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Author : Manuel Amunategui
language : en
Publisher: Apress
Release Date : 2018-09-12

Monetizing Machine Learning written by Manuel Amunategui and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-12 with Computers categories.

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 ideas Create 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 content Create dashboards with paywalls to offer subscription-based access Access 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.

Machine Learning Applications Using Python

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Author : Puneet Mathur
language : en
Publisher: Apress
Release Date : 2018-12-12

Machine Learning Applications Using Python written by Puneet Mathur and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Computers categories.

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 Learn Discover 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.

Monetizing Your Data

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Author : Andrew Roman Wells
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-27

Monetizing Your Data written by Andrew Roman Wells 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 2017-02-27 with Business & Economics categories.

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.

Machine Learning Design Patterns

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Author : Valliappa Lakshmanan
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-15

Machine Learning Design Patterns written by Valliappa Lakshmanan and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with Computers categories.

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

Monetizing Your Data

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Author : Andrew Roman Wells
language : en
Publisher: John Wiley & Sons
Release Date : 2017-03-13

Monetizing Mobile Apps Revenue Models And Marketing Secrets For Sustained Growth

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Author : Favour Emeli
language : en
Publisher: Recorded Books
Release Date : 2025-01-29

Monetizing Mobile Apps Revenue Models And Marketing Secrets For Sustained Growth written by Favour Emeli and has been published by Recorded Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-29 with Business & Economics categories.

Monetizing Mobile Apps: Revenue Models and Marketing Secrets for Sustained Growth Building a mobile app is just the beginning—turning it into a profitable venture is where the real challenge lies. Monetizing Mobile Apps is your ultimate guide to creating multiple revenue streams and scaling your app’s growth sustainably. This book walks you through the most effective revenue models, from in-app purchases and subscriptions to ad-based monetization and premium offerings. You’ll learn how to select the right monetization strategy for your app, maximize your app’s potential, and ensure that it continues to generate consistent income over time. Beyond just revenue models, this book dives deep into the marketing strategies that will help your app stand out in a crowded market. Learn how to attract users, retain them, and build brand loyalty through effective marketing tactics, including app store optimization (ASO), social media campaigns, and influencer partnerships. With real-world case studies, expert tips, and actionable insights, Monetizing Mobile Apps gives you the tools to not only launch your app successfully but also grow it into a long-term, sustainable business. Whether you're developing a gaming app, productivity tool, or lifestyle platform, this book helps you unlock the full revenue potential of your mobile app.

Machine Learning And Security

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Author : Clarence Chio
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-01-26

Machine Learning And Security written by Clarence Chio and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-26 with Computers categories.

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

Monetizing Data

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Author : Stephan Liozu
language : en
Publisher: Ulaga & Associés
Release Date : 2018-10-30

Monetizing Data written by Stephan Liozu and has been published by Ulaga & Associés this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-30 with Business & Economics categories.

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

Machine Learning With Core Ml

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Author : Joshua Newnham
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-28

Machine Learning With Core Ml written by Joshua Newnham 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 2018-06-28 with Computers categories.

Leverage the power of Apple's Core ML to create smart iOS apps Key Features Explore the concepts of machine learning and Apple’s Core ML APIs Use Core ML to understand and transform images and videos Exploit the power of using CNN and RNN in iOS applications Book Description Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs What you will learn Understand components of an ML project using algorithms, problems, and data Master Core ML by obtaining and importing machine learning model, and generate classes Prepare data for machine learning model and interpret results for optimized solutions Create and optimize custom layers for unsupported layers Apply CoreML to image and video data using CNN Learn the qualities of RNN to recognize sketches, and augment drawing Use Core ML transfer learning to execute style transfer on images Who this book is for Machine Learning with Core ML is for you if you are an intermediate iOS developer interested in applying machine learning to your mobile apps. This book is also for those who are machine learning developers or deep learning practitioners who want to bring the power of neural networks in their iOS apps. Some exposure to machine learning concepts would be beneficial but not essential, as this book acts as a launchpad into the world of machine learning for developers.

Ai Monetization Blueprint

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Author : Dr. Ope Banwo
language : en
Publisher: Dr Ope Banwo
Release Date : 2024-07-10

Ai Monetization Blueprint written by Dr. Ope Banwo and has been published by Dr Ope Banwo this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-10 with Business & Economics categories.

Welcome to "AI Monetization Blueprint: 99 Surefire Ways to Monetize AI Without Tears" by Dr. Ope Banwo. In an era where artificial intelligence (AI) is transforming industries and reshaping the future, the potential to monetize this powerful technology is vast and largely untapped. This book serves as your definitive guide to unlocking the financial opportunities presented by AI, providing you with 99 proven strategies to turn AI into a lucrative venture.

Monetizing Machine Learning

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