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Machine Learning for the Web

Machine Learning for the Web

By : Steve Essinger, Isoni
4.5 (27)
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Machine Learning for the Web

Machine Learning for the Web

4.5 (27)
By: Steve Essinger, Isoni

Overview of this book

Python is a general purpose and also a comparatively easy to learn programming language. Hence it is the language of choice for data scientists to prototype, visualize, and run data analyses on small and medium-sized data sets. This is a unique book that helps bridge the gap between machine learning and web development. It focuses on the difficulties of implementing predictive analytics in web applications. We focus on the Python language, frameworks, tools, and libraries, showing you how to build a machine learning system. You will explore the core machine learning concepts and then develop and deploy the data into a web application using the Django framework. You will also learn to carry out web, document, and server mining tasks, and build recommendation engines. Later, you will explore Python’s impressive Django framework and will find out how to build a modern simple web app with machine learning features.
Table of Contents (10 chapters)
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9
Index

Admin interface and API


In order to manage the data of the application, the admin interface and an API point can be set. From the admin panel we can see both the movie's data, and the user registered, writing the following admin.py file:

from django.contrib import admin
from books_recsys_app.models import MovieData,UserProfile
      
class MoviesAdmin(admin.ModelAdmin):
      list_display = ['title', 'description']

admin.site.register(UserProfile)
admin.site.register(MovieData,MoviesAdmin)

After setting the corresponding admin URL on the urls.py file:

url(r'^admin/', include(admin.site.urls))

We should see our admin panel (at http://localhost:8000/admin/) with the two models and the data within the models resembles the fields specified in the admin.py file:

To set the API endpoint to retrieve the data for each registered user, first we need to write out serializers.py specifying which fields of the UserProfile model we want to employ:

from books_recsys_app.models import UserProfile
from rest_framework...
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Machine Learning for the Web
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