Recommendation System & Recommendation Engine With Python

Master recommendation systems with recommendation techniques and methodologies using Python

What you'll learn

Learn concepts of Recommendation Engine

Learn the techniques used by companies like Netflix to recommend movies to the customer

Be able to build a simple but functional Recommendation Engine

Learn recommending movies, books using the recommendation system.

Learn about Collaborative based filtering.

Requirements

Basics of Python

Anaconda and Python installed in pc

Description

Learn about recommendation system. Also known as recommender engines. Recommendation Engines are everywhere. Netflix, Amazon and YouTube to name a few. Then there is the Ultimate Recommendation Engine: Google. Recommendation Engines help us make choices suited to our personal tastes.Recommender systems aim to predict users’ interests and recommend product items that quite likely are 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 themselves. The object of this course is for you to walk away with a solid understanding of the fundamentals behind the Collaborative filtering algorithm used by companies like Netflix or Amazon Prime to recommend movies to users based on the tastes of other similar users. According to Netflix, there 70% of the videos seen by recommending the videos to the user. Not only Netflix, Amazon also claims most products, they because of their recommendation system. There is a wide range of techniques to be used to build recommender engines. In this learning path, It will mostly cover all the easy to moderate kind of techniques with hands on experience.Two types of Recommendation systems are Collaborative Based and Content based filters Recommending system. You'll be excel both the methods after the completion of course. Recommendation Engines will be essential to selling anything and Big Companies are already looking on new ways to use them and for developers and marketeers who understand them. This course will give you a fundamental, conceptual understanding of how Recommendation Engines work by walking you through building a simple toy Recommendation Engine from scratch using simple math and basic python programming skills. Taking this course is an easy way to prepare for more advance study as concepts are explained in plain language and code is walked through line by line.

Overview

Section 1: Recommendation Engine - Basics

Lecture 1 Introduction to Project

Lecture 2 Collaborative Filtering

Lecture 3 Anaconda Setup Dataset Download

Lecture 4 Surprise Data frame

Lecture 5 Cross Validation Model

Lecture 6 Train Test Prediction

Lecture 7 Function For Prediction

Lecture 8 Movie Prediction

Section 2: Project On Recommendation Engine: Book Recommender

Lecture 9 Introduction to Project

Lecture 10 Case Study

Lecture 11 Numerical Cols

Lecture 12 Functions

Lecture 13 Rename Notebook

Lecture 14 Variable Name

Lecture 15 Publication Date

Lecture 16 Developing function

Lecture 17 Sort Book

Lecture 18 Content Based

Lecture 19 Feature Extraction

Lecture 20 Content Recommender

Lecture 21 Import Data

Lecture 22 Soup Function

Lecture 23 Reset Index Function

Section 3: Project On Recommendation Engine: Advanced Book Recommender

Lecture 24 Introduction to Project

Lecture 25 Enter a New Book Name

Lecture 26 Users Data

Lecture 27 Baseline

Lecture 28 Users ID

Lecture 29 User ID Column

Lecture 30 Book ID Index

Lecture 31 Import Pandas

Lecture 32 Hybrid

Lecture 33 Import NumPy

Lecture 34 Hybrid Model

Section 4: Develop A Movie Recommendation Engine

Lecture 35 Intro to Develop A Movie Recommendation Engine

Lecture 36 Importing Libraries for the Project

Lecture 37 Simple Recommender

Lecture 38 Simple Recommender Continue

Lecture 39 Content Based Recommender

Lecture 40 Content Based Recommender Continue

Any professional who want to know the secrets behind the recommendation of the products,Python beginners looking for interesting projects