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| 01-Part 1 Introduction.mp4 |
21.31Мб |
| 02-Chapter 1 Machine learning and graphs - An introduction.mp4 |
69.70Мб |
| 03-Chapter 1 Business understanding.mp4 |
39.10Мб |
| 04-Chapter 1 Machine learning challenges.mp4 |
49.84Мб |
| 05-Chapter 1 Performance.mp4 |
53.14Мб |
| 06-Chapter 1 Graphs.mp4 |
33.32Мб |
| 07-Chapter 1 Graphs as models of networks.mp4 |
71.29Мб |
| 08-Chapter 1 The role of graphs in machine learning.mp4 |
73.83Мб |
| 09-Chapter 2 Graph data engineering.mp4 |
82.01Мб |
| 1. Get Free Premium Accounts Daily On Our Discord Server!.txt |
1.32Кб |
| 10-Chapter 2 Velocity.mp4 |
50.81Мб |
| 11-Chapter 2 Graphs in the big data platform.mp4 |
49.38Мб |
| 12-Chapter 2 Graphs are valuable for big data.mp4 |
43.18Мб |
| 13-Chapter 2 Graphs are valuable for master data management.mp4 |
75.67Мб |
| 14-Chapter 2 Graph databases.mp4 |
52.12Мб |
| 15-Chapter 2 Sharding.mp4 |
70.52Мб |
| 16-Chapter 2 Native vs. non-native graph databases.mp4 |
79.92Мб |
| 17-Chapter 2 Label property graphs.mp4 |
37.69Мб |
| 18-Chapter 3 Graphs in machine learning applications.mp4 |
65.87Мб |
| 19-Chapter 3 Managing data sources.mp4 |
77.36Мб |
| 2. OneHack.us Premium Cracked Accounts-Tutorials-Guides-Articles Community Based Forum.url |
377б |
| 20-Chapter 3 Detect a fraud.mp4 |
52.33Мб |
| 21-Chapter 3 Recommend items.mp4 |
63.56Мб |
| 22-Chapter 3 Algorithms.mp4 |
48.19Мб |
| 23-Chapter 3 Find keywords in a document.mp4 |
53.60Мб |
| 24-Chapter 3 Storing and accessing machine learning models.mp4 |
31.38Мб |
| 25-Chapter 3 Monitoring a subject.mp4 |
55.54Мб |
| 26-Chapter 3 Visualization.mp4 |
37.90Мб |
| 27-Chapter 3 Leftover - Deep learning and graph neural networks.mp4 |
52.78Мб |
| 28-Part 2 Recommendations.mp4 |
148.91Мб |
| 29-Chapter 4 Content-based recommendations.mp4 |
67.48Мб |
| 3. FTUApps.com Download Cracked Developers Applications For Free.url |
239б |
| 30-Chapter 4 Representing item features.mp4 |
63.39Мб |
| 31-Chapter 4 Representing item features.mp4 |
60.23Мб |
| 32-Chapter 4 User modeling.mp4 |
33.57Мб |
| 33-Chapter 4 Providing recommendations.mp4 |
56.79Мб |
| 34-Chapter 4 Providing recommendations.mp4 |
66.34Мб |
| 35-Chapter 4 Providing recommendations.mp4 |
72.60Мб |
| 36-Chapter 5 Collaborative filtering.mp4 |
98.97Мб |
| 37-Chapter 5 Collaborative filtering recommendations.mp4 |
92.75Мб |
| 38-Chapter 5 Computing the nearest neighbor network.mp4 |
69.04Мб |
| 39-Chapter 5 Computing the nearest neighbor network.mp4 |
47.87Мб |
| 4. FreeCoursesOnline.io Download Udacity, Masterclass, Lynda, PHLearn, etc Free.url |
290б |
| 40-Chapter 5 Providing recommendations.mp4 |
53.76Мб |
| 41-Chapter 5 Dealing with the cold-start problem.mp4 |
40.18Мб |
| 42-Chapter 6 Session-based recommendations.mp4 |
61.79Мб |
| 43-Chapter 6 The events chain and the session graph.mp4 |
68.35Мб |
| 44-Chapter 6 Providing recommendations.mp4 |
81.30Мб |
| 45-Chapter 6 Session-based k-NN.mp4 |
63.60Мб |
| 46-Chapter 7 Context-aware and hybrid recommendations.mp4 |
67.60Мб |
| 47-Chapter 7 Representing contextual information.mp4 |
42.88Мб |
| 48-Chapter 7 Providing recommendations.mp4 |
85.94Мб |
| 49-Chapter 7 Providing recommendations.mp4 |
85.12Мб |
| 50-Chapter 7 Advantages of the graph approach.mp4 |
51.81Мб |
| 51-Chapter 7 Providing recommendations.mp4 |
38.56Мб |
| 52-Part 3 Fighting fraud.mp4 |
34.38Мб |
| 53-Chapter 8 Basic approaches to graph-powered fraud detection.mp4 |
48.49Мб |
| 54-Chapter 8 Fraud prevention and detection.mp4 |
45.24Мб |
| 55-Chapter 8 The role of graphs in fighting fraud.mp4 |
47.11Мб |
| 56-Chapter 8 Warm-up - Basic approaches.mp4 |
55.49Мб |
| 57-Chapter 8 Identifying a fraud ring.mp4 |
46.91Мб |
| 58-Chapter 9 Proximity-based algorithms.mp4 |
68.99Мб |
| 59-Chapter 9 Distance-based approach.mp4 |
49.88Мб |
| 60-Chapter 9 Creating the k-nearest neighbors graph.mp4 |
52.11Мб |
| 61-Chapter 9 Identifying fraudulent transactions.mp4 |
82.58Мб |
| 62-Chapter 9 Identifying fraudulent transactions.mp4 |
32.51Мб |
| 63-Chapter 10 Social network analysis against fraud.mp4 |
79.64Мб |
| 64-Chapter 10 Social network analysis concepts.mp4 |
46.44Мб |
| 65-Chapter 10 Score-based methods.mp4 |
32.24Мб |
| 66-Chapter 10 Neighborhood metrics.mp4 |
45.87Мб |
| 67-Chapter 10 Centrality metrics.mp4 |
61.27Мб |
| 68-Chapter 10 Collective inference algorithms.mp4 |
50.60Мб |
| 69-Chapter 10 Cluster-based methods.mp4 |
65.65Мб |
| 70-Part 4 Taming text with graphs.mp4 |
24.45Мб |
| 71-Chapter 11 Graph-based natural language processing.mp4 |
57.65Мб |
| 72-Chapter 11 A basic approach - Store and access sequence of words.mp4 |
53.54Мб |
| 73-Chapter 11 NLP and graphs.mp4 |
80.48Мб |
| 74-Chapter 11 NLP and graphs.mp4 |
70.02Мб |
| 75-Chapter 12 Knowledge graphs.mp4 |
60.09Мб |
| 76-Chapter 12 Knowledge graph building - Entities.mp4 |
94.08Мб |
| 77-Chapter 12 Knowledge graph building - Relationships.mp4 |
68.65Мб |
| 78-Chapter 12 Semantic networks.mp4 |
38.36Мб |
| 79-Chapter 12 Unsupervised keyword extraction.mp4 |
52.87Мб |
| 80-Chapter 12 Unsupervised keyword extraction.mp4 |
35.89Мб |
| 81-Chapter 12 Keyword co-occurrence graph.mp4 |
50.57Мб |
| 82-Appendix A. Machine learning algorithms taxonomy.mp4 |
65.16Мб |
| 83-Appendix C Graphs for processing patterns and workflows.mp4 |
43.83Мб |
| 84-Appendix C Graphs for defining complex processing workflows.mp4 |
50.43Мб |
| 85-Appendix D. Representing graphs.mp4 |
40.52Мб |