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种子名称： [FreeTutorials.Eu] [UDEMY] Recommender Systems and Deep Learning in Python - [FTU]
文件类型： 视频
文件数目： 82个文件
文件大小： 4.03 GB
收录时间： 2019-6-17 19:42
已经下载： 3次
资源热度： 151
最近下载： 2024-6-30 08:41

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[FreeTutorials.Eu] [UDEMY] Recommender Systems and Deep Learning in Python - [FTU].torrent

1. Welcome/1. Introduction.mp421.63MB

1. Welcome/2. Outline of the course.mp434.19MB

1. Welcome/3. Where to get the code.mp427.14MB

2. Simple Recommendation Systems/10. Bayesian Approach part 2 (Sampling and Ranking).mp424.5MB

2. Simple Recommendation Systems/11. Bayesian Approach part 3 (Gaussian).mp432.72MB

2. Simple Recommendation Systems/12. Bayesian Approach part 4 (Code).mp4106.51MB

2. Simple Recommendation Systems/13. Demographics and Supervised Learning.mp448.57MB

2. Simple Recommendation Systems/14. PageRank (part 1).mp454.89MB

2. Simple Recommendation Systems/15. PageRank (part 2).mp449.92MB

2. Simple Recommendation Systems/16. Evaluating a Ranking.mp434.93MB

2. Simple Recommendation Systems/17. Section Conclusion.mp431.01MB

2. Simple Recommendation Systems/1. Section Introduction and Outline.mp427.25MB

2. Simple Recommendation Systems/2. Perspective for this Section.mp418.29MB

2. Simple Recommendation Systems/3. Basic Intuitions.mp430.62MB

2. Simple Recommendation Systems/4. Associations.mp429.89MB

2. Simple Recommendation Systems/5. Hacker News - Will you be penalized for talking about the NSA.mp437.63MB

2. Simple Recommendation Systems/6. Reddit - Should censorship based on politics be allowed.mp453.07MB

2. Simple Recommendation Systems/7. Problems with Average Rating _ Explore vs. Exploit (part 1).mp447.72MB

2. Simple Recommendation Systems/8. Problems with Average Rating _ Explore vs. Exploit (part 2).mp445.62MB

2. Simple Recommendation Systems/9. Bayesian Approach part 1 (Optional).mp444.95MB

3. Collaborative Filtering/1. Collaborative Filtering Section Introduction.mp451.63MB

3. Collaborative Filtering/2. User-User Collaborative Filtering.mp460.69MB

3. Collaborative Filtering/3. Collaborative Filtering Exercise Prep.mp443.58MB

3. Collaborative Filtering/4. Data Preprocessing.mp4115.91MB

3. Collaborative Filtering/5. User-User Collaborative Filtering in Code.mp4153.58MB

3. Collaborative Filtering/6. Item-Item Collaborative Filtering.mp447.58MB

3. Collaborative Filtering/7. Item-Item Collaborative Filtering in Code.mp469.46MB

3. Collaborative Filtering/8. Collaborative Filtering Section Conclusion.mp429.35MB

4. Matrix Factorization and Deep Learning/10. Probabilistic Matrix Factorization.mp422.96MB

4. Matrix Factorization and Deep Learning/11. Bayesian Matrix Factorization.mp420.72MB

4. Matrix Factorization and Deep Learning/12. Matrix Factorization in Keras (Discussion).mp432.24MB

4. Matrix Factorization and Deep Learning/13. Matrix Factorization in Keras (Code).mp463.94MB

4. Matrix Factorization and Deep Learning/14. Deep Neural Network (Discussion).mp414.98MB

4. Matrix Factorization and Deep Learning/15. Deep Neural Network (Code).mp425.1MB

4. Matrix Factorization and Deep Learning/16. Residual Learning (Discussion).mp47.54MB

4. Matrix Factorization and Deep Learning/17. Residual Learning (Code).mp417.22MB

4. Matrix Factorization and Deep Learning/18. Autoencoders (AutoRec) Discussion.mp448.9MB

4. Matrix Factorization and Deep Learning/19. Autoencoders (AutoRec) Code.mp4102.31MB

4. Matrix Factorization and Deep Learning/1. Matrix Factorization Section Introduction.mp416.87MB

4. Matrix Factorization and Deep Learning/2. Matrix Factorization - First Steps.mp468.68MB

4. Matrix Factorization and Deep Learning/3. Matrix Factorization - Training.mp432.59MB

4. Matrix Factorization and Deep Learning/4. Matrix Factorization - Expanding Our Model.mp433.72MB

4. Matrix Factorization and Deep Learning/5. Matrix Factorization - Regularization.mp422.35MB

4. Matrix Factorization and Deep Learning/6. Matrix Factorization - Exercise Prompt.mp44.25MB

4. Matrix Factorization and Deep Learning/7. Matrix Factorization in Code.mp452.37MB

4. Matrix Factorization and Deep Learning/8. Matrix Factorization in Code - Vectorized.mp497.37MB

4. Matrix Factorization and Deep Learning/9. SVD (Singular Value Decomposition).mp432.63MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/10. RBM Code pt 1.mp470.43MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/11. RBM Code pt 2.mp439.57MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/12. RBM Code pt 3.mp4128.54MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/13. Speeding up the RBM Code.mp482.94MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/1. RBMs for Collaborative Filtering Section Introduction.mp410.32MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/2. Intro to RBMs.mp439.44MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/3. Motivation Behind RBMs.mp434.01MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/4. Intractability.mp412.92MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/5. Neural Network Equations.mp431.7MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/6. Training an RBM (part 1).mp449.06MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/7. Training an RBM (part 2).mp427.33MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/8. Training an RBM (part 3) - Free Energy.mp427.57MB

5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/9. Categorical RBM for Recommender System Ratings.mp447.59MB

6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/1. Big Data and Spark Section Introduction.mp435.54MB

6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/2. Setting up Spark in your Local Environment.mp434.66MB

6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/3. Matrix Factorization in Spark.mp4110.01MB

6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/4. Spark Submit.mp456.06MB

6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/5. Setting up a Spark Cluster on AWS EC2.mp473.23MB

6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/6. Making Predictions in the Real World.mp411.31MB

7. Basics Review/1. Keras Discussion.mp427.64MB

7. Basics Review/2. Keras Neural Network in Code.mp466.17MB

7. Basics Review/3. Keras Functional API.mp438.64MB

7. Basics Review/4. Confidence Intervals (Appendix).mp439.83MB

7. Basics Review/5. Gaussian Conjugate Prior (Appendix).mp425.13MB

8. Appendix/10. Python 2 vs Python 3.mp419.11MB

8. Appendix/11. BONUS Where to get discount coupons and FREE deep learning material.mp413.37MB

8. Appendix/1. What is the Appendix.mp418.09MB

8. Appendix/2. Windows-Focused Environment Setup 2018.mp4194.28MB

8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4167MB

8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4117.3MB

8. Appendix/5. How to Succeed in this Course (Long Version).mp439.24MB

8. Appendix/6. How to Code by Yourself (part 1).mp482.52MB

8. Appendix/7. How to Code by Yourself (part 2).mp456.66MB

8. Appendix/8. What order should I take your courses in (part 1).mp488.42MB

8. Appendix/9. What order should I take your courses in (part 2).mp4123.03MB