首页 磁力链接怎么用

Building Recommender Systems with Machine Learning and AI

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 2020-10-22 23:07 2024-5-21 04:10 162 4.45 GB 109
二维码链接
Building Recommender Systems with Machine Learning and AI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!
文件列表
  1. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/4. [Activity] Playing with Tensorflow.mp4145.56MB
  2. Building Recommender Systems with Machine Learning and AI/1. Getting Started/1. Udemy 101 Getting the Most From This Course.mp419.71MB
  3. Building Recommender Systems with Machine Learning and AI/1. Getting Started/2. [Activity] Install Anaconda, course materials, and create movie recommendations!.mp4104.08MB
  4. Building Recommender Systems with Machine Learning and AI/1. Getting Started/3. Course Roadmap.mp427.58MB
  5. Building Recommender Systems with Machine Learning and AI/1. Getting Started/4. Types of Recommenders.mp426.82MB
  6. Building Recommender Systems with Machine Learning and AI/1. Getting Started/5. Understanding You through Implicit and Explicit Ratings.mp420.72MB
  7. Building Recommender Systems with Machine Learning and AI/1. Getting Started/6. Top-N Recommender Architecture.mp437.09MB
  8. Building Recommender Systems with Machine Learning and AI/1. Getting Started/7. [Quiz] Review the basics of recommender systems..mp421.3MB
  9. Building Recommender Systems with Machine Learning and AI/2. Introduction to Python [Optional]/1. [Activity] The Basics of Python.mp443.03MB
  10. Building Recommender Systems with Machine Learning and AI/2. Introduction to Python [Optional]/2. Data Structures in Python.mp424.41MB
  11. Building Recommender Systems with Machine Learning and AI/2. Introduction to Python [Optional]/3. Functions in Python.mp412.27MB
  12. Building Recommender Systems with Machine Learning and AI/2. Introduction to Python [Optional]/4. [Exercise] Booleans, loops, and a hands-on challenge.mp413.86MB
  13. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/1. TrainTest and Cross Validation.mp429.05MB
  14. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/2. Accuracy Metrics (RMSE, MAE).mp440.28MB
  15. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/3. Top-N Hit Rate - Many Ways.mp424.53MB
  16. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/4. Coverage, Diversity, and Novelty.mp413.73MB
  17. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/5. Churn, Responsiveness, and AB Tests.mp460.94MB
  18. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/6. [Quiz] Review ways to measure your recommender..mp412.83MB
  19. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/7. [Activity] Walkthrough of RecommenderMetrics.py.mp464.3MB
  20. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/8. [Activity] Walkthrough of TestMetrics.py.mp454.36MB
  21. Building Recommender Systems with Machine Learning and AI/3. Evaluating Recommender Systems/9. [Activity] Measure the Performance of SVD Recommendations.mp421.56MB
  22. Building Recommender Systems with Machine Learning and AI/4. A Recommender Engine Framework/1. Our Recommender Engine Architecture.mp432.73MB
  23. Building Recommender Systems with Machine Learning and AI/4. A Recommender Engine Framework/2. [Activity] Recommender Engine Walkthrough, Part 1.mp437.88MB
  24. Building Recommender Systems with Machine Learning and AI/4. A Recommender Engine Framework/3. [Activity] Recommender Engine Walkthrough, Part 2.mp439.59MB
  25. Building Recommender Systems with Machine Learning and AI/4. A Recommender Engine Framework/4. [Activity] Review the Results of our Algorithm Evaluation..mp434.57MB
  26. Building Recommender Systems with Machine Learning and AI/5. Content-Based Filtering/1. Content-Based Recommendations, and the Cosine Similarity Metric.mp461.59MB
  27. Building Recommender Systems with Machine Learning and AI/5. Content-Based Filtering/2. K-Nearest-Neighbors and Content Recs.mp419.61MB
  28. Building Recommender Systems with Machine Learning and AI/5. Content-Based Filtering/3. [Activity] Producing and Evaluating Content-Based Movie Recommendations.mp452.36MB
  29. Building Recommender Systems with Machine Learning and AI/5. Content-Based Filtering/4. [Activity] Bleeding Edge Alert! Mise en Scene Recommendations.mp446.52MB
  30. Building Recommender Systems with Machine Learning and AI/5. Content-Based Filtering/5. [Exercise] Dive Deeper into Content-Based Recommendations.mp424.11MB
  31. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/1. Measuring Similarity, and Sparsity.mp459.1MB
  32. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/2. Similarity Metrics.mp430.68MB
  33. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/3. User-based Collaborative Filtering.mp434.21MB
  34. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/4. [Activity] User-based Collaborative Filtering, Hands-On.mp448.61MB
  35. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/5. Item-based Collaborative Filtering.mp452.26MB
  36. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/6. [Activity] Item-based Collaborative Filtering, Hands-On.mp426.81MB
  37. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/7. [Exercise] Tuning Collaborative Filtering Algorithms.mp419.7MB
  38. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/8. [Activity] Evaluating Collaborative Filtering Systems Offline.mp415.43MB
  39. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/9. [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering.mp49.5MB
  40. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/10. KNN Recommenders.mp424.85MB
  41. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/11. [Activity] Running User and Item-Based KNN on MovieLens.mp423.76MB
  42. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/12. [Exercise] Experiment with different KNN parameters..mp441.26MB
  43. Building Recommender Systems with Machine Learning and AI/6. Neighborhood-Based Collaborative Filtering/13. Bleeding Edge Alert! Translation-Based Recommendations.mp421.29MB
  44. Building Recommender Systems with Machine Learning and AI/7. Matrix Factorization Methods/1. Principal Component Analysis (PCA).mp461.2MB
  45. Building Recommender Systems with Machine Learning and AI/7. Matrix Factorization Methods/2. Singular Value Decomposition.mp424.3MB
  46. Building Recommender Systems with Machine Learning and AI/7. Matrix Factorization Methods/3. [Activity] Running SVD and SVD++ on MovieLens.mp437.49MB
  47. Building Recommender Systems with Machine Learning and AI/7. Matrix Factorization Methods/4. Improving on SVD.mp423.07MB
  48. Building Recommender Systems with Machine Learning and AI/7. Matrix Factorization Methods/5. [Exercise] Tune the hyperparameters on SVD.mp411.86MB
  49. Building Recommender Systems with Machine Learning and AI/7. Matrix Factorization Methods/6. Bleeding Edge Alert! Sparse Linear Methods (SLIM).mp426.47MB
  50. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/1. Deep Learning Introduction.mp417.62MB
  51. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/2. Deep Learning Pre-Requisites.mp437.05MB
  52. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/3. History of Artificial Neural Networks.mp484.21MB
  53. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/5. Training Neural Networks.mp438.35MB
  54. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/6. Tuning Neural Networks.mp431.04MB
  55. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/7. Introduction to Tensorflow.mp492.48MB
  56. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/8. [Activity] Handwriting Recognition with Tensorflow, part 1.mp490.96MB
  57. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/9. [Activity] Handwriting Recognition with Tensorflow, part 2.mp490.9MB
  58. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/10. [Activity] Handwriting Recognition with Tensorflow, Part 3.mp450.36MB
  59. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/11. Introduction to Keras.mp416.45MB
  60. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/12. [Activity] Handwriting Recognition with Keras.mp488.49MB
  61. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/13. Classifier Patterns with Keras.mp424.84MB
  62. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/14. [Exercise] Predict Political Parties of Politicians with Keras.mp4100.21MB
  63. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/15. Intro to Convolutional Neural Networks (CNN's).mp478.19MB
  64. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/16. CNN Architectures.mp422.54MB
  65. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/17. [Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp482.28MB
  66. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/18. Intro to Recurrent Neural Networks (RNN's).mp449.64MB
  67. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/19. Training Recurrent Neural Networks.mp420.72MB
  68. Building Recommender Systems with Machine Learning and AI/8. Introduction to Deep Learning [Optional]/20. [Activity] Sentiment Analysis of Movie Reviews using RNN's and Keras.mp4119.79MB
  69. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/1. Intro to Deep Learning for Recommenders.mp442.66MB
  70. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/2. Restricted Boltzmann Machines (RBM's).mp431.67MB
  71. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/3. [Activity] Recommendations with RBM's, part 1.mp4144.44MB
  72. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/4. [Activity] Recommendations with RBM's, part 2.mp476.73MB
  73. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/5. [Activity] Evaluating the RBM Recommender.mp437.67MB
  74. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/6. [Exercise] Tuning Restricted Boltzmann Machines.mp433.61MB
  75. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/7. Exercise Results Tuning a RBM Recommender.mp411.85MB
  76. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/8. Auto-Encoders for Recommendations Deep Learning for Recs.mp426.92MB
  77. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/9. [Activity] Recommendations with Deep Neural Networks.mp475.41MB
  78. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/10. Clickstream Recommendations with RNN's.mp448.72MB
  79. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/11. [Exercise] Get GRU4Rec Working on your Desktop.mp47.46MB
  80. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/12. Exercise Results GRU4Rec in Action.mp462.65MB
  81. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/13. Bleeding Edge Alert! Deep Factorization Machines.mp457.36MB
  82. Building Recommender Systems with Machine Learning and AI/9. Deep Learning for Recommender Systems/14. More Emerging Tech to Watch.mp427.64MB
  83. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/1. [Activity] Introduction and Installation of Apache Spark.mp453.3MB
  84. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/2. Apache Spark Architecture.mp417.36MB
  85. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/3. [Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.mp455.61MB
  86. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/4. [Activity] Recommendations from 20 million ratings with Spark.mp450.67MB
  87. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/5. Amazon DSSTNE.mp442.31MB
  88. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/6. DSSTNE in Action.mp4113.66MB
  89. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/7. Scaling Up DSSTNE.mp410.44MB
  90. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/8. AWS SageMaker and Factorization Machines.mp415.58MB
  91. Building Recommender Systems with Machine Learning and AI/10. Scaling it Up/9. SageMaker in Action Factorization Machines on one million ratings, in the cloud.mp468.34MB
  92. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/1. The Cold Start Problem (and solutions).mp427.79MB
  93. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/2. [Exercise] Implement Random Exploration.mp42.2MB
  94. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/3. Exercise Solution Random Exploration.mp424.17MB
  95. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/4. Stoplists.mp419.91MB
  96. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/5. [Exercise] Implement a Stoplist.mp41.35MB
  97. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/6. Exercise Solution Implement a Stoplist.mp426.71MB
  98. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/7. Filter Bubbles, Trust, and Outliers.mp492.41MB
  99. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/8. [Exercise] Identify and Eliminate Outlier Users.mp41.77MB
  100. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/9. Exercise Solution Outlier Removal.mp438.49MB
  101. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/10. Fraud, The Perils of Clickstream, and International Concerns.mp458.23MB
  102. Building Recommender Systems with Machine Learning and AI/11. Real-World Challenges of Recommender Systems/11. Temporal Effects, and Value-Aware Recommendations.mp454.03MB
  103. Building Recommender Systems with Machine Learning and AI/12. Case Studies/1. Case Study YouTube, Part 1.mp426.91MB
  104. Building Recommender Systems with Machine Learning and AI/12. Case Studies/2. Case Study YouTube, Part 2.mp426.26MB
  105. Building Recommender Systems with Machine Learning and AI/12. Case Studies/3. Case Study Netflix, Part 1.mp427.55MB
  106. Building Recommender Systems with Machine Learning and AI/12. Case Studies/4. Case Study Netflix, Part 2.mp426.57MB
  107. Building Recommender Systems with Machine Learning and AI/13. Hybrid Approaches/1. Hybrid Recommenders and Exercise.mp418.4MB
  108. Building Recommender Systems with Machine Learning and AI/13. Hybrid Approaches/2. Exercise Solution Hybrid Recommenders.mp433.18MB
  109. Building Recommender Systems with Machine Learning and AI/14. Wrapping Up/1. More to Explore.mp438.93MB
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