Update docs/ai_plan.md
Browse files- docs/ai_plan.md +95 -0
docs/ai_plan.md
CHANGED
|
@@ -921,6 +921,101 @@ Beyond the factors provided, the following additional factors can enhance job re
|
|
| 921 |
|
| 922 |
---
|
| 923 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 924 |
# Conclusion
|
| 925 |
|
| 926 |
Implementing these AI/ML functionalities will significantly enhance the efficiency and effectiveness of the Hostel Grievance Redressal System. By leveraging advanced technologies like reinforcement learning, transformer-based models, and anomaly detection algorithms, and by integrating them within a Flask API framework, the system will provide a more responsive, empathetic, and proactive approach to managing resident grievances. Proper data collection, preprocessing, model training, and continuous monitoring are crucial to the success of these implementations. Following the detailed steps outlined above will ensure a robust and scalable integration of AI/ML capabilities into the existing system.
|
|
|
|
| 921 |
|
| 922 |
---
|
| 923 |
|
| 924 |
+
# Directory Structure
|
| 925 |
+
```
|
| 926 |
+
|
| 927 |
+
Hostel-Management-and-Greivance-Redressal-System/
|
| 928 |
+
├── .env
|
| 929 |
+
├── Dockerfile
|
| 930 |
+
├── a.py
|
| 931 |
+
├── app.py
|
| 932 |
+
├── dir_structure.md
|
| 933 |
+
├── docs.md
|
| 934 |
+
├── readme.md
|
| 935 |
+
├── requirements.txt
|
| 936 |
+
├── routes.py
|
| 937 |
+
├── space.yml
|
| 938 |
+
├── test_endpoints.py
|
| 939 |
+
├── config/
|
| 940 |
+
│ ├── __init__.py
|
| 941 |
+
│ ├── config.py
|
| 942 |
+
├── docs/
|
| 943 |
+
│ ├── README.md
|
| 944 |
+
│ ├── a.md
|
| 945 |
+
│ ├── ai_plan.md
|
| 946 |
+
│ ├── basic.md
|
| 947 |
+
│ ├── data_plan.md
|
| 948 |
+
│ ├── docs.md
|
| 949 |
+
│ ├── plan.txt
|
| 950 |
+
│ ├── ppt.md
|
| 951 |
+
│ ├── project_report.md
|
| 952 |
+
├── models/
|
| 953 |
+
│ ├── intelligent_routing/
|
| 954 |
+
│ │ ├── docs.md
|
| 955 |
+
│ │ ├── generate_data.py
|
| 956 |
+
│ │ ├── model.py
|
| 957 |
+
│ │ ├── test_model.py
|
| 958 |
+
│ │ ├── train.py
|
| 959 |
+
│ │ ├── saved_model/
|
| 960 |
+
│ │ │ ├── model.keras
|
| 961 |
+
│ │ ├── test_data/
|
| 962 |
+
│ │ │ ├── __init__.py
|
| 963 |
+
│ │ │ ├── test_data.json
|
| 964 |
+
│ │ ├── test_results/
|
| 965 |
+
│ │ │ ├── confusion_matrix.png
|
| 966 |
+
│ │ │ ├── roc_curve.png
|
| 967 |
+
│ │ │ ├── test_report.json
|
| 968 |
+
│ │ ├── train_data/
|
| 969 |
+
│ │ │ ├── __init__.py
|
| 970 |
+
│ │ │ ├── training_data.json
|
| 971 |
+
│ ├── job_recommendation/
|
| 972 |
+
│ │ ├── docs.md
|
| 973 |
+
│ │ ├── generate_data.py
|
| 974 |
+
│ │ ├── model.py
|
| 975 |
+
│ │ ├── test.py
|
| 976 |
+
│ │ ├── train.py
|
| 977 |
+
│ │ ├── saved_model/
|
| 978 |
+
│ │ │ ├── model.keras
|
| 979 |
+
│ │ ├── test_data/
|
| 980 |
+
│ │ │ ├── __init__.py
|
| 981 |
+
│ │ │ ├── test_data.json
|
| 982 |
+
│ │ ├── test_results/
|
| 983 |
+
│ │ │ ├── test_report.json
|
| 984 |
+
│ │ ├── train_data/
|
| 985 |
+
│ │ │ ├── __init__.py
|
| 986 |
+
│ │ │ ├── training_data.json
|
| 987 |
+
│ ├── multilingual_translation/
|
| 988 |
+
│ │ ├── model.py
|
| 989 |
+
│ │ ├── test_model.py
|
| 990 |
+
│ │ ├── test_data/
|
| 991 |
+
│ │ │ ├── __init__.py
|
| 992 |
+
│ │ │ ├── test_data.json
|
| 993 |
+
│ │ ├── test_results/
|
| 994 |
+
│ │ │ ├── test_report.json
|
| 995 |
+
│ │ ├── train_data/
|
| 996 |
+
│ │ │ ├── __init__.py
|
| 997 |
+
│ │ │ ├── training_data.json
|
| 998 |
+
│ ├── sentiment_analysis/
|
| 999 |
+
│ │ ├── model.py
|
| 1000 |
+
│ │ ├── test_model.py
|
| 1001 |
+
│ │ ├── test_data/
|
| 1002 |
+
│ │ │ ├── __init__.py
|
| 1003 |
+
│ │ │ ├── test_data.json
|
| 1004 |
+
│ │ ├── test_results/
|
| 1005 |
+
│ │ │ ├── test_report.json
|
| 1006 |
+
│ │ ├── train_data/
|
| 1007 |
+
│ │ │ ├── __init__.py
|
| 1008 |
+
│ │ │ ├── training_data.json
|
| 1009 |
+
├── test_results/
|
| 1010 |
+
│ ├── endpoint_test_results.json
|
| 1011 |
+
├── test_results1/
|
| 1012 |
+
│ ├── endpoint_test_results.json
|
| 1013 |
+
├── utils/
|
| 1014 |
+
│ ├── __init__.py
|
| 1015 |
+
│ ├── dir_str_creater.py
|
| 1016 |
+
│ ├── logger.py
|
| 1017 |
+
```
|
| 1018 |
+
|
| 1019 |
# Conclusion
|
| 1020 |
|
| 1021 |
Implementing these AI/ML functionalities will significantly enhance the efficiency and effectiveness of the Hostel Grievance Redressal System. By leveraging advanced technologies like reinforcement learning, transformer-based models, and anomaly detection algorithms, and by integrating them within a Flask API framework, the system will provide a more responsive, empathetic, and proactive approach to managing resident grievances. Proper data collection, preprocessing, model training, and continuous monitoring are crucial to the success of these implementations. Following the detailed steps outlined above will ensure a robust and scalable integration of AI/ML capabilities into the existing system.
|