Название: Python WebApp: Learn how to serve a Machine Learning Model predicting car prices Автор: Nicolas Maignan
Издательство: Amazon.com Services LLC
Год: 2020
Язык: английский
Формат: pdf, azw3, epub
Размер: 10.1 MB
When you'll go through this book, you will learn how to turn an idea into a web application serving a Machine Learning model. The chosen use case is Second-hand Car Pricing for which we'll go from having no data to deploying a small web application serving a Machine Learning Regressor trained to predict car prices. We'll do this using mainly Python (Quart, LGBM, Pandas, Scikit-learn), a little bit of HTLM, CSS, JS, and Docker (Docker-compose).
The goal of this book is to take you through the journey that I, author of this book, followed. This journey, despite being initially guided by my indecision, led to a drastic improvement in my programming skills and an increase in my value as a developer. The point of this book is for you to be able to replicate the process on your own use case, which you are free to define according to your own centers of interest or to your latest concerns. If you go through the following pages, you will learn how to create a Car Price Prediction Web-Application serving the results of a Machine-Learning model using the following frameworks:
• Python
• Environment control: Conda, Pip
• Quality control: Mypy, Flake8, Black
• Web crawling/scraping: Selenium
• General data science: Pandas, LightGBM, Scikit-learn
• Web-Applications: Quart (similar to Sanic, Flask, Django, etc.)
• DevOps
• App containerization: Docker
• Deployment: Docker-compose
Luckily enough, I had already been introduced to the wonders of Data Science, Web Scraping, Machine Learning and DevOps. And it is faced with the idea of spending a new weekend of active but fruitless research that I decided to solve my problem in a slightly overkill way.
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