Recommender Systems with Machine Learning

سرفصل های دوره

Build Recommender Systems for Real World Applications using Machine Learning

1. Introduction

1. AI Sciences Introduction

2. Instructor Introduction

3. Overview of Recommender Systems

4. Fundamentals of Recommender Systems

5. Project Overview

6. Request for Your Honest Review

7. Links for the Course's Materials and Codes.html

2. Motivation for Recommender System

1. Links for the Course's Materials and Codes.html

2. Recommender Systems Overview

3. Introduction to Recommender Systems

4. Recommender Systems Process and Goals

5. Generations of Recommender Systems

6. Nexus of AI and Reccommender Systems

7. Applications and Real World Challenges

8. Deep content-based recommender systems belong to the which generation.html

9. Which processsystem is used behind the spotify new song suggestion.html

10. Companies use recommender systems to boost their …… primarily.html

11. What is the primary goal of recommender systems.html

12. Which are the challenges for recommender systems.html

3. Basic of Recommender System

1. Links for the Course's Materials and Codes.html

2. Overview

3. Taxanomy of Recommender Systems

4. ICM

5. User Rating Matrix

6. Quality of Recommender System

7. Online Evaluation Techniques

8. Offline Evaluation Techniques

9. Data Partitioning

10. Important Parameters

11. Error Metric Computation

12. Content Based Filtering

13. Collaborative Filtering and User Based Collaborative Filtering

14. Item Model and Memory Based Collaborative Filtering

15. The values in the item content matrix are in.html

16. Online evaluation techniques for recommender systems are based on.html

17. Why are recommendation engines becoming popular.html

18. What are the challenges in Content Based Filtering.html

19. What are different Recommendation Engine techniques.html

4. Machine Learning for Recommender System

1. Links for the Course's Materials and Codes.html

2. Overview

3. Benifits of Machine Learning

4. Guidelines for ML

5. Design Approaches for ML

6. Content Based Filtering

7. Data Prepration for Content Based Filtering

8. Data Manipulation for Content Based Filtering

9. Exploring Genres in Content Based Filtering

10. tf-idf Matrix

11. Recommendation Engine

12. Making Recommendations

13. Item Based Collaborative Filtering

14. Item Based Filtering Data Prepration

15. Age Distribution for Users

16. Collaborative Filtering using KNN

17. Geographic Filtering

18. KNN Implementation

19. Making Recommendations with Collaborative Filtering

20. User Based Collaborative Filtering

21. Identify the correct recommendation system's algorithm(s) from given options.html

22. Which of the following businesses would be least likely to use Machine Learning based Recommendation Engine.html

23. What are the key features of User-driven strategies.html

24. Machine Learning based recommender systems identify which of the following behavioral attributes of the customers.html

25. Benefits of machine learning for recommender systems include.html

5. Project 1 Song Recommendation System using content based filtering

1. Links for the Course's Materials and Codes.html

2. Project Introduction

3. Dataset Usage

4. Missing Values

5. Exploring Genres

6. Occurence Count

7. tf-idf Implementation

8. Similarity Index

9. Fuzzywuzzy Implementaion

10. Find Closest Title

11. Making Recommendations

6. Project 2 Movie Recommendation System using collaborative filtering

1. Links for the Course's Materials and Codes.html

2. Project Introduction

3. Dataset Discussion

4. Rating Plot

5. Count

6. Logrithm of Count

7. Active Users and Popular Movies

8. Create Collaborative Filter

9. KNN Implementation

10. Making Recommendations

11. THANK YOU Bonus Video

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تولید کننده: Udemy-Training