easy way to build django recommendation

Question

Please i am new to machine learning,done with more than 11 hours of video tutorials but still not clear yet, please how can i build a recommendation system with django because i need to deliver a project before the end of this month.Please help me. i have already study django-recommends but still not clear.

class Loopnote(models.Model):
    user=models.ForeignKey(AUTH_USER_MODEL,on_delete=models.CASCADE)
    body=models.TextField()
    created=models.DateTimeField(auto_now_add=True)
    like=models.ManyToManyField(AUTH_USER_MODEL,related_name='like')
    share = models.PositiveIntegerField(default=0)
    loop=models.IntegerField(null=True,blank=True)
    # comments = GenericRelation(Comment)
    # comments=models.ManyToManyField('Comment',null=True,blank=True)
    video=models.FileField(upload_to='Videos/',null=True, blank=True)
    photo=models.ImageField(upload_to='LoopPhotos/',null=True, blank=True)
    class Meta:
        verbose_name_plural = 'Loopnotes'
        ordering= ['-created']
        get_latest_by = "-created"


    def __str__(self):
        return "%s loopnote" % self.user
    def get_absolute_url(self):
        return reverse('loopnote_detail', args=[str(self.pk)])

That is the model table that i will like to use recommendation for. Thanks in advance.

Answer 1

Django is a web framework that can allow queries to DB, not a tool intended for machine learning. You'll need to train the algorithm using another tool and then use that model in Django for inference only. Very crude points for you to follow now:

1. Train a model using Keras or another ML library
2. Put that model in your Django project
3. Fetch data from the DB using Django and feed that into the Keras model
4. Display results using Django views