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
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