Gangmin Li

Computer Science

1. Models 100%
2. Big Data 33%
3. User 29%
4. Records 24%
5. Language Modeling 21%
6. Bidirectional Encoder Representations From Transformers 21%
7. Machine Learning 20%
8. Large Language Model 20%
9. Medical Diagnosis 17%
10. Data Ingestion 15%
11. Accuracy 13%
12. Lambda Architecture 13%
13. Intents 13%
14. Bidirectional Long Short-Term Memory Network 13%
15. Named Entity Recognition 13%
16. Convolutional Neural Network 13%
17. Embedding 13%
18. Reinforcement Learning 13%
19. Model 11%
20. Diagnosis 10%
21. Change Pattern 10%
22. Model Benchmark 10%
23. Performance Enhancement 10%
24. Temporal Dynamic 10%
25. Electronic Medical Record 9%
26. Relationships 9%
27. Events 9%
28. Domain Knowledge 9%
29. Domains 9%
30. Personal Relation 6%
31. Trend Analysis 6%
32. Common Sense Knowledge 6%
33. Graph Convolutional Network 6%
34. Natural-Language Understanding 6%
35. Root Cause Analysis 6%
36. Vectors 6%
37. Multiple-Criteria Decision Analysis 6%
38. Heterogeneous Data 6%
39. Data Performance 6%
40. Memory Model 6%
41. multi agent 6%
42. Web Application 6%
43. Analytics 6%
44. Gradient Boosting 6%
45. Deep Neural Network 6%
46. Dynamic Pricing 6%
47. Abstractive Summarization 6%
48. Attention (Machine Learning) 6%
49. Detection 6%
50. Data Stream Processing 6%