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Develop Recommendation Engine with PYTHON

person icon Pranjal Srivastava

4.3

Develop Recommendation Engine with PYTHON

Learn to apply recommendation techniques used by Amazon, Netflix, Youtube, IMDB

updated on icon Updated on Jun, 2025

language icon Language - English

person icon Pranjal Srivastava

English [CC]

category icon Development ,Data Science,Machine Learning

Lectures -12

Duration -58 mins

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4.3

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Course Description

In this course, you'll going to learn about a recommendation system. Also known as recommender engines. According to Netflix, 70% of the videos are seen by recommending videos to the user. Not only Netflix, but Amazon also claims most products, because of their recommendation system. There is a wide range of techniques to be used to build recommender engines. This learning path will mostly cover all the easy-to-moderate kinds of techniques with hands-on experience.

What is a Recommendation System?

Recommender systems aim to predict users’ interests and recommend product items that are quite likely to be interesting for them. They are among the most powerful machine learning systems that online retailers implement in order to drive sales. Data required for recommender systems stems from explicit user ratings after watching a movie or listening to a song, from implicit search engine queries and purchase histories, or from other knowledge about the users/items themselves.

Two types of Recommendation systems are Collaborative Based and Content-based filters, Recommending systems. You'll excel in both methods after the completion of the course. Other than this, you'll also learn more about cosine, Pearson correlation, as well as different types of machine learning algorithms like Logistic regression and K-nearest neighbours to get the best recommendation.

Goals

  • Learn the Collaborative Filtering Recommendation technique.
  • Learn Content-Based Filtering Recommendation technique.
  • Learn to build Hybrid Recommendation Engine.
  • Learn the techniques used by Amazon, Netflix to recommend products to the customer.

Prerequisites

  • Anaconda installed in pc.
  • Python is installed in pc.
  • A little bit of knowledge of Python programming, pandas and numpy.
Develop Recommendation Engine with PYTHON

Curriculum

Check out the detailed breakdown of what’s inside the course

Everything is Recommendation

1 Lectures
  • play icon What is Recommendation System? 02:31 02:31

Let's create a basic Recommendation System..

4 Lectures
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Content Filter Recommendation System

3 Lectures
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Collaboration Based Recommendation System

3 Lectures
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Instructor Details

Pranjal Srivastava

Pranjal Srivastava

I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer.

I have authored 78 courses with over 115,000 students worldwide across 175+ countries on wide array of technologies like devops, containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.

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