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cover of the book Monetizing machine learning: quickly turn Python ML ideas into web applications on the serverless cloud

Ebook: Monetizing machine learning: quickly turn Python ML ideas into web applications on the serverless cloud

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06.02.2024
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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.;Chapter 1 Introduction to Serverless Technologies -- Chapter 2 Client-Side Intelligence using Regression Coefficients on Azure -- Chapter 3 Real-Time Intelligence with Logistic Regression on GCP -- Chapter 4 Pre-Trained Intelligence with Gradient Boosting Machine on AWS -- Chapter 5 Case Study Part 1: Supporting Both Web and Mobile Browsers -- Chapter 6 Displaying Predictions with Google Maps on Azure -- Chapter 7 Forecasting with Naive Bayes and OpenWeather on AWS -- Chapter 8 Interactive Drawing Canvas and Digit Predictions using TensorFlow on GCP -- Chapter 9 Case Study Part 2: Displaying Dynamic Charts -- Chapter 10 Recommending with Singular Value Decomposition on GCP -- Chapter 11 Simplifying Complex Concepts with NLP and Visualization on Azure -- Chapter 12 Case Study Part 3: Enriching Content with Fundamental Financial Information -- Chapter 13 Google Analytics -- Chapter 14 A/B Testing on PythonAnywhere and MySQL -- Chapter 15 From Visitor To Subscriber -- Chapter 16 Case Study Part 4: Building a Subscription Paywall with Memberful -- Chapter 17 Conclusion.-.
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