[FreeCoursesOnline.io] MANNING - Graph-Powered Machine Learning [Video Edition] - 磁力管家

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种子哈希：0de85e2eb7e10c2a64eb479f64f61eee47b23b48
文档大小：5.2 GB
文档个数：89个文档
下载次数：1602次
下载速度：极快
收录时间：2023-12-20
最近下载：2025-05-14
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文档列表

28-Part 2 Recommendations.mp4 156.1 MB
36-Chapter 5 Collaborative filtering.mp4 103.8 MB
76-Chapter 12 Knowledge graph building - Entities.mp4 98.7 MB
37-Chapter 5 Collaborative filtering recommendations.mp4 97.3 MB
48-Chapter 7 Providing recommendations.mp4 90.1 MB
49-Chapter 7 Providing recommendations.mp4 89.3 MB
61-Chapter 9 Identifying fraudulent transactions.mp4 86.6 MB
09-Chapter 2 Graph data engineering.mp4 86.0 MB
44-Chapter 6 Providing recommendations.mp4 85.3 MB
73-Chapter 11 NLP and graphs.mp4 84.4 MB
16-Chapter 2 Native vs. non-native graph databases.mp4 83.8 MB
63-Chapter 10 Social network analysis against fraud.mp4 83.5 MB
19-Chapter 3 Managing data sources.mp4 81.1 MB
13-Chapter 2 Graphs are valuable for master data management.mp4 79.3 MB
08-Chapter 1 The role of graphs in machine learning.mp4 77.4 MB
35-Chapter 4 Providing recommendations.mp4 76.1 MB
07-Chapter 1 Graphs as models of networks.mp4 74.8 MB
15-Chapter 2 Sharding.mp4 73.9 MB
74-Chapter 11 NLP and graphs.mp4 73.4 MB
02-Chapter 1 Machine learning and graphs - An introduction.mp4 73.1 MB
38-Chapter 5 Computing the nearest neighbor network.mp4 72.4 MB
58-Chapter 9 Proximity-based algorithms.mp4 72.3 MB
77-Chapter 12 Knowledge graph building - Relationships.mp4 72.0 MB
43-Chapter 6 The events chain and the session graph.mp4 71.7 MB
46-Chapter 7 Context-aware and hybrid recommendations.mp4 70.9 MB
29-Chapter 4 Content-based recommendations.mp4 70.8 MB
34-Chapter 4 Providing recommendations.mp4 69.6 MB
18-Chapter 3 Graphs in machine learning applications.mp4 69.1 MB
69-Chapter 10 Cluster-based methods.mp4 68.8 MB
82-Appendix A. Machine learning algorithms taxonomy.mp4 68.3 MB
45-Chapter 6 Session-based k-NN.mp4 66.7 MB
21-Chapter 3 Recommend items.mp4 66.6 MB
30-Chapter 4 Representing item features.mp4 66.5 MB
42-Chapter 6 Session-based recommendations.mp4 64.8 MB
67-Chapter 10 Centrality metrics.mp4 64.2 MB
31-Chapter 4 Representing item features.mp4 63.2 MB
75-Chapter 12 Knowledge graphs.mp4 63.0 MB
71-Chapter 11 Graph-based natural language processing.mp4 60.5 MB
33-Chapter 4 Providing recommendations.mp4 59.5 MB
25-Chapter 3 Monitoring a subject.mp4 58.2 MB
56-Chapter 8 Warm-up - Basic approaches.mp4 58.2 MB
40-Chapter 5 Providing recommendations.mp4 56.4 MB
23-Chapter 3 Find keywords in a document.mp4 56.2 MB
72-Chapter 11 A basic approach - Store and access sequence of words.mp4 56.1 MB
05-Chapter 1 Performance.mp4 55.7 MB
79-Chapter 12 Unsupervised keyword extraction.mp4 55.4 MB
27-Chapter 3 Leftover - Deep learning and graph neural networks.mp4 55.3 MB
20-Chapter 3 Detect a fraud.mp4 54.9 MB
14-Chapter 2 Graph databases.mp4 54.7 MB
60-Chapter 9 Creating the k-nearest neighbors graph.mp4 54.6 MB
50-Chapter 7 Advantages of the graph approach.mp4 54.3 MB
10-Chapter 2 Velocity.mp4 53.3 MB
68-Chapter 10 Collective inference algorithms.mp4 53.1 MB
81-Chapter 12 Keyword co-occurrence graph.mp4 53.0 MB
84-Appendix C Graphs for defining complex processing workflows.mp4 52.9 MB
59-Chapter 9 Distance-based approach.mp4 52.3 MB
04-Chapter 1 Machine learning challenges.mp4 52.3 MB
11-Chapter 2 Graphs in the big data platform.mp4 51.8 MB
53-Chapter 8 Basic approaches to graph-powered fraud detection.mp4 50.8 MB
22-Chapter 3 Algorithms.mp4 50.5 MB
39-Chapter 5 Computing the nearest neighbor network.mp4 50.2 MB
55-Chapter 8 The role of graphs in fighting fraud.mp4 49.4 MB
57-Chapter 8 Identifying a fraud ring.mp4 49.2 MB
64-Chapter 10 Social network analysis concepts.mp4 48.7 MB
66-Chapter 10 Neighborhood metrics.mp4 48.1 MB
54-Chapter 8 Fraud prevention and detection.mp4 47.4 MB
83-Appendix C Graphs for processing patterns and workflows.mp4 46.0 MB
12-Chapter 2 Graphs are valuable for big data.mp4 45.3 MB
47-Chapter 7 Representing contextual information.mp4 45.0 MB
85-Appendix D. Representing graphs.mp4 42.5 MB
41-Chapter 5 Dealing with the cold-start problem.mp4 42.1 MB
03-Chapter 1 Business understanding.mp4 41.0 MB
51-Chapter 7 Providing recommendations.mp4 40.4 MB
78-Chapter 12 Semantic networks.mp4 40.2 MB
26-Chapter 3 Visualization.mp4 39.7 MB
17-Chapter 2 Label property graphs.mp4 39.5 MB
80-Chapter 12 Unsupervised keyword extraction.mp4 37.6 MB
52-Part 3 Fighting fraud.mp4 36.1 MB
32-Chapter 4 User modeling.mp4 35.2 MB
06-Chapter 1 Graphs.mp4 34.9 MB
62-Chapter 9 Identifying fraudulent transactions.mp4 34.1 MB
65-Chapter 10 Score-based methods.mp4 33.8 MB
24-Chapter 3 Storing and accessing machine learning models.mp4 32.9 MB
70-Part 4 Taming text with graphs.mp4 25.6 MB
01-Part 1 Introduction.mp4 22.3 MB
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