Download Manning | Graph-Powered Machine Learning [Video Edition] [FCO] Torrent

Torrent Contents Size: 4.8 GB

Manning | Graph-Powered Machine Learning [Video Edition] [FCO]

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01-Part 1 Introduction.mp4	MP4	21.3 MB
02-Chapter 1 Machine learning and graphs - An introduction.mp4	MP4	69.7 MB
03-Chapter 1 Business understanding.mp4	MP4	39.1 MB
04-Chapter 1 Machine learning challenges.mp4	MP4	49.8 MB
05-Chapter 1 Performance.mp4	MP4	53.1 MB
06-Chapter 1 Graphs.mp4	MP4	33.3 MB
07-Chapter 1 Graphs as models of networks.mp4	MP4	71.3 MB
08-Chapter 1 The role of graphs in machine learning.mp4	MP4	73.8 MB
09-Chapter 2 Graph data engineering.mp4	MP4	82 MB
1. Get Free Premium Accounts Daily On Our Discord Server!.txt	TXT	1.3 KB
10-Chapter 2 Velocity.mp4	MP4	50.8 MB
11-Chapter 2 Graphs in the big data platform.mp4	MP4	49.4 MB
12-Chapter 2 Graphs are valuable for big data.mp4	MP4	43.2 MB
13-Chapter 2 Graphs are valuable for master data management.mp4	MP4	75.7 MB
14-Chapter 2 Graph databases.mp4	MP4	52.1 MB
15-Chapter 2 Sharding.mp4	MP4	70.5 MB
16-Chapter 2 Native vs. non-native graph databases.mp4	MP4	79.9 MB
17-Chapter 2 Label property graphs.mp4	MP4	37.7 MB
18-Chapter 3 Graphs in machine learning applications.mp4	MP4	65.9 MB
19-Chapter 3 Managing data sources.mp4	MP4	77.4 MB
2. OneHack.us Premium Cracked Accounts-Tutorials-Guides-Articles Community Based Forum.url	URL	409.6 B
20-Chapter 3 Detect a fraud.mp4	MP4	52.3 MB
21-Chapter 3 Recommend items.mp4	MP4	63.6 MB
22-Chapter 3 Algorithms.mp4	MP4	48.2 MB
23-Chapter 3 Find keywords in a document.mp4	MP4	53.6 MB
24-Chapter 3 Storing and accessing machine learning models.mp4	MP4	31.4 MB
25-Chapter 3 Monitoring a subject.mp4	MP4	55.5 MB
26-Chapter 3 Visualization.mp4	MP4	37.9 MB
27-Chapter 3 Leftover - Deep learning and graph neural networks.mp4	MP4	52.8 MB
28-Part 2 Recommendations.mp4	MP4	148.9 MB
29-Chapter 4 Content-based recommendations.mp4	MP4	67.5 MB
3. FTUApps.com Download Cracked Developers Applications For Free.url	URL	204.8 B
30-Chapter 4 Representing item features.mp4	MP4	63.4 MB
31-Chapter 4 Representing item features.mp4	MP4	60.2 MB
32-Chapter 4 User modeling.mp4	MP4	33.6 MB
33-Chapter 4 Providing recommendations.mp4	MP4	56.8 MB
34-Chapter 4 Providing recommendations.mp4	MP4	66.3 MB
35-Chapter 4 Providing recommendations.mp4	MP4	72.6 MB
36-Chapter 5 Collaborative filtering.mp4	MP4	99 MB
37-Chapter 5 Collaborative filtering recommendations.mp4	MP4	92.7 MB
38-Chapter 5 Computing the nearest neighbor network.mp4	MP4	69 MB
39-Chapter 5 Computing the nearest neighbor network.mp4	MP4	47.9 MB
4. FreeCoursesOnline.io Download Udacity, Masterclass, Lynda, PHLearn, etc Free.url	URL	307.2 B
40-Chapter 5 Providing recommendations.mp4	MP4	53.8 MB
41-Chapter 5 Dealing with the cold-start problem.mp4	MP4	40.2 MB
42-Chapter 6 Session-based recommendations.mp4	MP4	61.8 MB
43-Chapter 6 The events chain and the session graph.mp4	MP4	68.3 MB
44-Chapter 6 Providing recommendations.mp4	MP4	81.3 MB
45-Chapter 6 Session-based k-NN.mp4	MP4	63.6 MB
46-Chapter 7 Context-aware and hybrid recommendations.mp4	MP4	67.6 MB
47-Chapter 7 Representing contextual information.mp4	MP4	42.9 MB
48-Chapter 7 Providing recommendations.mp4	MP4	85.9 MB
49-Chapter 7 Providing recommendations.mp4	MP4	85.1 MB
50-Chapter 7 Advantages of the graph approach.mp4	MP4	51.8 MB
51-Chapter 7 Providing recommendations.mp4	MP4	38.6 MB
52-Part 3 Fighting fraud.mp4	MP4	34.4 MB
53-Chapter 8 Basic approaches to graph-powered fraud detection.mp4	MP4	48.5 MB
54-Chapter 8 Fraud prevention and detection.mp4	MP4	45.2 MB
55-Chapter 8 The role of graphs in fighting fraud.mp4	MP4	47.1 MB
56-Chapter 8 Warm-up - Basic approaches.mp4	MP4	55.5 MB
57-Chapter 8 Identifying a fraud ring.mp4	MP4	46.9 MB
58-Chapter 9 Proximity-based algorithms.mp4	MP4	69 MB
59-Chapter 9 Distance-based approach.mp4	MP4	49.9 MB
60-Chapter 9 Creating the k-nearest neighbors graph.mp4	MP4	52.1 MB
61-Chapter 9 Identifying fraudulent transactions.mp4	MP4	82.6 MB
62-Chapter 9 Identifying fraudulent transactions.mp4	MP4	32.5 MB
63-Chapter 10 Social network analysis against fraud.mp4	MP4	79.6 MB
64-Chapter 10 Social network analysis concepts.mp4	MP4	46.4 MB
65-Chapter 10 Score-based methods.mp4	MP4	32.2 MB
66-Chapter 10 Neighborhood metrics.mp4	MP4	45.9 MB
67-Chapter 10 Centrality metrics.mp4	MP4	61.3 MB
68-Chapter 10 Collective inference algorithms.mp4	MP4	50.6 MB
69-Chapter 10 Cluster-based methods.mp4	MP4	65.7 MB
70-Part 4 Taming text with graphs.mp4	MP4	24.5 MB
71-Chapter 11 Graph-based natural language processing.mp4	MP4	57.7 MB
72-Chapter 11 A basic approach - Store and access sequence of words.mp4	MP4	53.5 MB
73-Chapter 11 NLP and graphs.mp4	MP4	80.5 MB
74-Chapter 11 NLP and graphs.mp4	MP4	70 MB
75-Chapter 12 Knowledge graphs.mp4	MP4	60.1 MB
76-Chapter 12 Knowledge graph building - Entities.mp4	MP4	94.1 MB
77-Chapter 12 Knowledge graph building - Relationships.mp4	MP4	68.6 MB
78-Chapter 12 Semantic networks.mp4	MP4	38.4 MB
79-Chapter 12 Unsupervised keyword extraction.mp4	MP4	52.9 MB
80-Chapter 12 Unsupervised keyword extraction.mp4	MP4	35.9 MB
81-Chapter 12 Keyword co-occurrence graph.mp4	MP4	50.6 MB
82-Appendix A. Machine learning algorithms taxonomy.mp4	MP4	65.2 MB
83-Appendix C Graphs for processing patterns and workflows.mp4	MP4	43.8 MB
84-Appendix C Graphs for defining complex processing workflows.mp4	MP4	50.4 MB
85-Appendix D. Representing graphs.mp4	MP4	40.5 MB

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Manning | Graph-Powered Machine Learning [Video Edition] [FCO]

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