What do you think?
Rate this book
Django and Machine Learning: Building Intelligent Web Applications
This book provides an in-depth guide to building intelligent web applications using Django and Machine Learning. The book starts with an overview of Django and its use in web development, as well as an introduction to Machine Learning and its applications. The benefits of combining Django and Machine Learning are then explored.
The book then moves on to setting up the development environment for Machine Learning in Django, including installing Python and Django, creating a virtual environment for the project, and installing required Machine Learning packages.
The creation of Machine Learning models is covered in Chapter 3, including understanding different Machine Learning models, designing and training a Machine Learning model using scikit-learn, and saving and loading the trained model in Django.
Chapter 4 focuses on integrating Machine Learning with Django, including implementing the trained Machine Learning model in Django, using the Django ORM to query the database and make predictions, and displaying Machine Learning predictions in Django templates.
Chapter 5 covers scaling Machine Learning with Django, including building an API for the Machine Learning model using Django Rest Framework (DRF), using Celery and Redis for asynchronous task processing in Django, and scaling the Machine Learning model with distributed computing using Apache Spark.
In Chapter 6, Machine Learning visualization with Django is explored, including integrating data visualization tools like Matplotlib and Seaborn in Django and creating interactive visualizations with Bokeh and Plotly in Django.
Chapter 7 focuses on building intelligent web applications with Django and Machine Learning, including implementing recommendation systems, building a sentiment analysis system, and developing a chatbot in Django with Machine Learning.
The book concludes with Chapter 8, covering deploying Django and Machine Learning applications to production, including preparing the project for deployment, configuring the production environment, and deploying the project to a production server.
Overall, this book provides a comprehensive guide to building intelligent web applications with Django and Machine Learning, and is a valuable resource for developers looking to incorporate Machine Learning into their web development projects.
The book then moves on to setting up the development environment for Machine Learning in Django, including installing Python and Django, creating a virtual environment for the project, and installing required Machine Learning packages.
The creation of Machine Learning models is covered in Chapter 3, including understanding different Machine Learning models, designing and training a Machine Learning model using scikit-learn, and saving and loading the trained model in Django.
Chapter 4 focuses on integrating Machine Learning with Django, including implementing the trained Machine Learning model in Django, using the Django ORM to query the database and make predictions, and displaying Machine Learning predictions in Django templates.
Chapter 5 covers scaling Machine Learning with Django, including building an API for the Machine Learning model using Django Rest Framework (DRF), using Celery and Redis for asynchronous task processing in Django, and scaling the Machine Learning model with distributed computing using Apache Spark.
In Chapter 6, Machine Learning visualization with Django is explored, including integrating data visualization tools like Matplotlib and Seaborn in Django and creating interactive visualizations with Bokeh and Plotly in Django.
Chapter 7 focuses on building intelligent web applications with Django and Machine Learning, including implementing recommendation systems, building a sentiment analysis system, and developing a chatbot in Django with Machine Learning.
The book concludes with Chapter 8, covering deploying Django and Machine Learning applications to production, including preparing the project for deployment, configuring the production environment, and deploying the project to a production server.
Overall, this book provides a comprehensive guide to building intelligent web applications with Django and Machine Learning, and is a valuable resource for developers looking to incorporate Machine Learning into their web development projects.
58 pages, Kindle Edition
Published March 9, 2023
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
No one has reviewed this book yet.