Let’s Make Recommendation Systems Easy with Live Projects



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What you’ll learn:
Recommendation Engine , Python, Data Science, Artificial Intelligence, Machine Learning
Natural Language Processing (NLP), Cosine Similarity
Requirements
Python Programming
Description
This Course is designed for all Data Science & Machine Learning students, who are looking to understand “How to Build a Recommendation System from Scratch”.
In this course you will master various recommendation engines including Popularity Based, Content Based, Collaborative Filtering, Singular Value Decomposition(SVD), NLP and much more.
In the course you will learn аbout:
What is Recommendation Systems
How Big Tech Companies are using it
Type of different Recommendation Systems
How to Implement these in Python
What are Popularity Based Recommendation System
What are Content Based Recommendation System
What are Bag Of Word(BoW)
What is TFidf
How Natural Language Processing is used in defining a Recommendation System
What is Collaborative Filtering Recommendation System
How Singular Value Decomposition (SVD) can be utilized in Recommendation Systems
What are the various advantages and disadvantages of Recommendation System
Building your own Recommendation System using Python Programming.
Who this course is for:
Software Developers, Data Scientists, Python Developers interested in learning and applying machine learning concepts using recommendation systems
Software Developers looking to transition into an e-commerce company
College students who are looking to learn a new technology and implement in final year projects.
In this course you will work on 3 projects on different industry grade recommendation engines and will implement the learnings form the course.
I can assure you will enjoy working on these projects.
Who this course is for
Learners who are looking to work as a Data Scientist
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