Udemy Recommender System With Machine Learning and Statistics
Seeders : 0 Leechers : 4
| Torrent Hash : | 60C86C8A983928ED255B65A070BE3A503E1C5BE9 |
| Torrent Added : | at Oct. 24, 2023, 4:21 p.m. in Other |
| Torrent Size : | 484.3 MB |
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Udemy Recommender System With Machine Learning and Statistics
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Udemy Recommender System With Machine Learning and Statistics
Get Bonus Downloads Here.url -
1. Why Business Needs Recommender Systems.mp4 -
1. Why Business Needs Recommender Systems.srt -
1. Roadmap of the Course.mp4 -
1. Roadmap of the Course.srt -
1. The Hypotheses Behind the Main Solutions of Recommender Systems.mp4 -
1. The Hypotheses Behind the Main Solutions of Recommender Systems.srt -
1. A Quick Eda on the Grocery Dataset.mp4 -
1. A Quick Eda on the Grocery Dataset.srt -
2. What Is Collaborative Filtering in Depth.mp4 -
2. What Is Collaborative Filtering in Depth.srt -
3. How to Build and Train Collaborative Filtering Model With Fast.ai.mp4 -
3. How to Build and Train Collaborative Filtering Model With Fast.ai.srt -
4. How to Visualize Latent Features Do Popular Items Have a Higher Bias.mp4 -
4. How to Visualize Latent Features Do Popular Items Have a Higher Bias.srt -
1. What Is the Definition of Popularity and What Is Support.mp4 -
1. What Is the Definition of Popularity and What Is Support.srt -
2. How to Encode an Item-Order Matrix.mp4 -
2. How to Encode an Item-Order Matrix.srt -
3. What Are Confidence and Lift.mp4 -
3. What Are Confidence and Lift.srt -
4. What Is Association Rule and How to Apply Apriori Algorithm.mp4 -
4. What Is Association Rule and How to Apply Apriori Algorithm.srt -
5. How to Evaluate Results With Selected Criteria.mp4 -
5. How to Evaluate Results With Selected Criteria.srt -
1. End-Of-Course Conclusion.mp4 -
1. End-Of-Course Conclusion.srt -
Bonus Resources.txt -
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Get Bonus Downloads Here.url -
180 bytes
1. Why Business Needs Recommender Systems.mp4 -
25.7 MB
1. Why Business Needs Recommender Systems.srt -
1.8 KB
1. Roadmap of the Course.mp4 -
3.5 MB
1. Roadmap of the Course.srt -
1.1 KB
1. The Hypotheses Behind the Main Solutions of Recommender Systems.mp4 -
66.5 MB
1. The Hypotheses Behind the Main Solutions of Recommender Systems.srt -
4.8 KB
1. A Quick Eda on the Grocery Dataset.mp4 -
49.3 MB
1. A Quick Eda on the Grocery Dataset.srt -
4.6 KB
2. What Is Collaborative Filtering in Depth.mp4 -
11.0 MB
2. What Is Collaborative Filtering in Depth.srt -
4.1 KB
3. How to Build and Train Collaborative Filtering Model With Fast.ai.mp4 -
90.3 MB
3. How to Build and Train Collaborative Filtering Model With Fast.ai.srt -
5.7 KB
4. How to Visualize Latent Features Do Popular Items Have a Higher Bias.mp4 -
85.1 MB
4. How to Visualize Latent Features Do Popular Items Have a Higher Bias.srt -
5.0 KB
1. What Is the Definition of Popularity and What Is Support.mp4 -
38.1 MB
1. What Is the Definition of Popularity and What Is Support.srt -
4.2 KB
2. How to Encode an Item-Order Matrix.mp4 -
31.2 MB
2. How to Encode an Item-Order Matrix.srt -
2.1 KB
3. What Are Confidence and Lift.mp4 -
23.8 MB
3. What Are Confidence and Lift.srt -
1.9 KB
4. What Is Association Rule and How to Apply Apriori Algorithm.mp4 -
10.5 MB
4. What Is Association Rule and How to Apply Apriori Algorithm.srt -
2.7 KB
5. How to Evaluate Results With Selected Criteria.mp4 -
42.7 MB
5. How to Evaluate Results With Selected Criteria.srt -
1.6 KB
1. End-Of-Course Conclusion.mp4 -
6.6 MB
1. End-Of-Course Conclusion.srt -
796 bytes
Bonus Resources.txt -
357 bytes
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