首页 磁力链接怎么用

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

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
视频 2019-6-17 19:42 2024-12-22 05:25 182 4.03 GB 82
磁力链接
magnet:?xt=urn:btih:1e9426569178176e4474f566414a93061df681bf
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjFlOTQyNjU2OTE3ODE3NmU0NDc0ZjU2NjQxNGE5MzA2MWRmNjgxYmZaWg==
二维码链接
[FreeTutorials.Eu] [UDEMY] Recommender Systems and Deep Learning in Python - [FTU]的二维码
种子下载(838888不存储任何种子文件)
种子下载线路1(迅雷)--推荐
种子下载线路2(比特彗星)
种子下载线路3(torcache)
3条线路均为国内外知名下载网站种子链接，内容跟本站无关！
相关链接

FreeTutorials Eu UDEMY Recommender Systems and Deep Learning in Python - FTU

文件列表
  1. 1. Welcome/1. Introduction.mp421.63MB
  2. 1. Welcome/2. Outline of the course.mp434.19MB
  3. 1. Welcome/3. Where to get the code.mp427.14MB
  4. 2. Simple Recommendation Systems/10. Bayesian Approach part 2 (Sampling and Ranking).mp424.5MB
  5. 2. Simple Recommendation Systems/11. Bayesian Approach part 3 (Gaussian).mp432.72MB
  6. 2. Simple Recommendation Systems/12. Bayesian Approach part 4 (Code).mp4106.51MB
  7. 2. Simple Recommendation Systems/13. Demographics and Supervised Learning.mp448.57MB
  8. 2. Simple Recommendation Systems/14. PageRank (part 1).mp454.89MB
  9. 2. Simple Recommendation Systems/15. PageRank (part 2).mp449.92MB
  10. 2. Simple Recommendation Systems/16. Evaluating a Ranking.mp434.93MB
  11. 2. Simple Recommendation Systems/17. Section Conclusion.mp431.01MB
  12. 2. Simple Recommendation Systems/1. Section Introduction and Outline.mp427.25MB
  13. 2. Simple Recommendation Systems/2. Perspective for this Section.mp418.29MB
  14. 2. Simple Recommendation Systems/3. Basic Intuitions.mp430.62MB
  15. 2. Simple Recommendation Systems/4. Associations.mp429.89MB
  16. 2. Simple Recommendation Systems/5. Hacker News - Will you be penalized for talking about the NSA.mp437.63MB
  17. 2. Simple Recommendation Systems/6. Reddit - Should censorship based on politics be allowed.mp453.07MB
  18. 2. Simple Recommendation Systems/7. Problems with Average Rating _ Explore vs. Exploit (part 1).mp447.72MB
  19. 2. Simple Recommendation Systems/8. Problems with Average Rating _ Explore vs. Exploit (part 2).mp445.62MB
  20. 2. Simple Recommendation Systems/9. Bayesian Approach part 1 (Optional).mp444.95MB
  21. 3. Collaborative Filtering/1. Collaborative Filtering Section Introduction.mp451.63MB
  22. 3. Collaborative Filtering/2. User-User Collaborative Filtering.mp460.69MB
  23. 3. Collaborative Filtering/3. Collaborative Filtering Exercise Prep.mp443.58MB
  24. 3. Collaborative Filtering/4. Data Preprocessing.mp4115.91MB
  25. 3. Collaborative Filtering/5. User-User Collaborative Filtering in Code.mp4153.58MB
  26. 3. Collaborative Filtering/6. Item-Item Collaborative Filtering.mp447.58MB
  27. 3. Collaborative Filtering/7. Item-Item Collaborative Filtering in Code.mp469.46MB
  28. 3. Collaborative Filtering/8. Collaborative Filtering Section Conclusion.mp429.35MB
  29. 4. Matrix Factorization and Deep Learning/10. Probabilistic Matrix Factorization.mp422.96MB
  30. 4. Matrix Factorization and Deep Learning/11. Bayesian Matrix Factorization.mp420.72MB
  31. 4. Matrix Factorization and Deep Learning/12. Matrix Factorization in Keras (Discussion).mp432.24MB
  32. 4. Matrix Factorization and Deep Learning/13. Matrix Factorization in Keras (Code).mp463.94MB
  33. 4. Matrix Factorization and Deep Learning/14. Deep Neural Network (Discussion).mp414.98MB
  34. 4. Matrix Factorization and Deep Learning/15. Deep Neural Network (Code).mp425.1MB
  35. 4. Matrix Factorization and Deep Learning/16. Residual Learning (Discussion).mp47.54MB
  36. 4. Matrix Factorization and Deep Learning/17. Residual Learning (Code).mp417.22MB
  37. 4. Matrix Factorization and Deep Learning/18. Autoencoders (AutoRec) Discussion.mp448.9MB
  38. 4. Matrix Factorization and Deep Learning/19. Autoencoders (AutoRec) Code.mp4102.31MB
  39. 4. Matrix Factorization and Deep Learning/1. Matrix Factorization Section Introduction.mp416.87MB
  40. 4. Matrix Factorization and Deep Learning/2. Matrix Factorization - First Steps.mp468.68MB
  41. 4. Matrix Factorization and Deep Learning/3. Matrix Factorization - Training.mp432.59MB
  42. 4. Matrix Factorization and Deep Learning/4. Matrix Factorization - Expanding Our Model.mp433.72MB
  43. 4. Matrix Factorization and Deep Learning/5. Matrix Factorization - Regularization.mp422.35MB
  44. 4. Matrix Factorization and Deep Learning/6. Matrix Factorization - Exercise Prompt.mp44.25MB
  45. 4. Matrix Factorization and Deep Learning/7. Matrix Factorization in Code.mp452.37MB
  46. 4. Matrix Factorization and Deep Learning/8. Matrix Factorization in Code - Vectorized.mp497.37MB
  47. 4. Matrix Factorization and Deep Learning/9. SVD (Singular Value Decomposition).mp432.63MB
  48. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/10. RBM Code pt 1.mp470.43MB
  49. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/11. RBM Code pt 2.mp439.57MB
  50. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/12. RBM Code pt 3.mp4128.54MB
  51. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/13. Speeding up the RBM Code.mp482.94MB
  52. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/1. RBMs for Collaborative Filtering Section Introduction.mp410.32MB
  53. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/2. Intro to RBMs.mp439.44MB
  54. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/3. Motivation Behind RBMs.mp434.01MB
  55. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/4. Intractability.mp412.92MB
  56. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/5. Neural Network Equations.mp431.7MB
  57. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/6. Training an RBM (part 1).mp449.06MB
  58. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/7. Training an RBM (part 2).mp427.33MB
  59. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/8. Training an RBM (part 3) - Free Energy.mp427.57MB
  60. 5. Restricted Boltzmann Machines (RBMs) for Collaborative Filtering/9. Categorical RBM for Recommender System Ratings.mp447.59MB
  61. 6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/1. Big Data and Spark Section Introduction.mp435.54MB
  62. 6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/2. Setting up Spark in your Local Environment.mp434.66MB
  63. 6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/3. Matrix Factorization in Spark.mp4110.01MB
  64. 6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/4. Spark Submit.mp456.06MB
  65. 6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/5. Setting up a Spark Cluster on AWS EC2.mp473.23MB
  66. 6. Big Data Matrix Factorization with Spark Cluster on AWS EC2/6. Making Predictions in the Real World.mp411.31MB
  67. 7. Basics Review/1. Keras Discussion.mp427.64MB
  68. 7. Basics Review/2. Keras Neural Network in Code.mp466.17MB
  69. 7. Basics Review/3. Keras Functional API.mp438.64MB
  70. 7. Basics Review/4. Confidence Intervals (Appendix).mp439.83MB
  71. 7. Basics Review/5. Gaussian Conjugate Prior (Appendix).mp425.13MB
  72. 8. Appendix/10. Python 2 vs Python 3.mp419.11MB
  73. 8. Appendix/11. BONUS Where to get discount coupons and FREE deep learning material.mp413.37MB
  74. 8. Appendix/1. What is the Appendix.mp418.09MB
  75. 8. Appendix/2. Windows-Focused Environment Setup 2018.mp4194.28MB
  76. 8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4167MB
  77. 8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4117.3MB
  78. 8. Appendix/5. How to Succeed in this Course (Long Version).mp439.24MB
  79. 8. Appendix/6. How to Code by Yourself (part 1).mp482.52MB
  80. 8. Appendix/7. How to Code by Yourself (part 2).mp456.66MB
  81. 8. Appendix/8. What order should I take your courses in (part 1).mp488.42MB
  82. 8. Appendix/9. What order should I take your courses in (part 2).mp4123.03MB
友情提示
不会用的朋友看这里 把磁力链接复制到离线下载，或者bt下载软件里即可下载文件，或者直接复制迅雷链接到迅雷里下载！ 亲，你造吗？将网页分享给您的基友，下载的人越多速度越快哦！

违规内容投诉邮箱：[email protected]

概述 838888磁力搜索是一个磁力链接搜索引擎，是学术研究的副产品，用于解决资源过度分散的问题 它通过BitTorrent协议加入DHT网络，实时的自动采集数据，仅存储文件的标题、大小、文件列表、文件标识符（磁力链接）等基础信息 838888磁力搜索不下载任何真实资源，无法判断资源的合法性及真实性，使用838888磁力搜索服务的用户需自行鉴别内容的真伪 838888磁力搜索不上传任何资源，不提供Tracker服务，不提供种子文件的下载，这意味着838888磁力搜索 838888磁力搜索是一个完全合法的系统
838888磁力链接 磁力链接bt种子搜索引擎磁力搜索 DMCA