Monetizing Machine Learning Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud
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...
| Autores principales: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Berkeley, CA :
Apress
2018.
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| Edición: | 1st ed. 2018. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630733006719 |
Tabla de Contenidos:
- 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.-.
