Recommendation System & Recommendation Engine with Python

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EDUCBA Bridging the Gap

4:59:35

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1. Recommendation Engine - Basics

1. Introduction to Project.mp4

05:50

2. Collaborative Filtering.mp4

04:32

3. Anaconda Setup Dataset Download.mp4

04:54

4. Surprise Data frame.mp4

07:48

5. Cross Validation Model.mp4

03:13

6. Train Test Prediction.mp4

03:55

7. Function For Prediction.mp4

08:35

8. Movie Prediction.mp4

04:56

2. Project On Recommendation Engine Book Recommender

1. Introduction to Project.mp4

05:57

2. Case Study.mp4

08:56

3. Numerical Cols.mp4

10:02

4. Functions.mp4

07:34

5. Rename Notebook.mp4

06:29

6. Variable Name.mp4

08:46

7. Publication Date.mp4

09:34

8. Developing function.mp4

07:43

9. Sort Book.mp4

07:58

10. Content Based.mp4

03:57

11. Feature Extraction.mp4

10:33

12. Content Recommender.mp4

05:00

13. Import Data.mp4

07:34

14. Soup Function.mp4

08:21

15. Reset Index Function.mp4

07:23

3. Project On Recommendation Engine Advanced Book Recommender

1. Introduction to Project.mp4

05:48

2. Enter a New Book Name.mp4

10:11

3. Users Data.mp4

06:12

4. Baseline.mp4

09:49

5. Users ID.mp4

06:11

6. User ID Column.mp4

04:56

7. Book ID Index.mp4

06:25

8. Import Pandas.mp4

13:56

9. Hybrid.mp4

08:50

10. Import NumPy.mp4

06:37

11. Hybrid Model.mp4

09:03

4. Develop A Movie Recommendation Engine

1. Intro to Develop A Movie Recommendation Engine.mp4

06:56

2. Importing Libraries for the Project.mp4

12:57

3. Simple Recommender.mp4

11:18

4. Simple Recommender Continue.mp4

06:15

5. Content Based Recommender.mp4

07:08

6. Content Based Recommender Continue.mp4

07:33

Description

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.

Who is this for?

Any professional who want to know the secrets behind the recommendation of the products

Python beginners looking for interesting projects

What You Need to Know?

Basics of Python

Anaconda and Python installed in pc

More details

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 usersâ€™ 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.
Who this course is for:
Any professional who want to know the secrets behind the recommendation of the products
Python beginners looking for interesting projects

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EDUCBA Bridging the Gap

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