https://github.com/wahidpanda/malware_detection_dl_model_with_98_percent_accuracy

Malware Detection Using Machine Learning and Deep Learning Algorithms where highest Accuracy get 95%
https://github.com/wahidpanda/malware_detection_dl_model_with_98_percent_accuracy

cybersecurity deeplearning machine-learning machine-learning-algorithms machine-learning-malware-detection malware-detection ml ransomware-detection threats xgboost

Last synced: 7 months ago
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Malware Detection Using Machine Learning and Deep Learning Algorithms where highest Accuracy get 95%

• Host: GitHub
• URL: https://github.com/wahidpanda/malware_detection_dl_model_with_98_percent_accuracy
• Owner: wahidpanda
• Created: 2023-12-05T13:15:51.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-05T13:35:46.000Z (almost 2 years ago)
• Last Synced: 2025-01-21T20:48:58.706Z (9 months ago)
• Topics: cybersecurity, deeplearning, machine-learning, machine-learning-algorithms, machine-learning-malware-detection, malware-detection, ml, ransomware-detection, threats, xgboost
• Language: Jupyter Notebook
• Homepage:
• Size: 366 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Malware_Detection_DL_MODEL_with_98%_ACCURACY

Malware Detection Using Machine Learning and Deep Learning Algorithms, where the highest Accuracy is 95% 

![Untitled-design-1-1024x576](https://github.com/wahidpanda/Malware_Detection_DL_MODEL_with_98-_ACCURACY/assets/110899864/1e021741-b067-49da-9485-acae73d31810)

Model used:

**1. RandomForestClassifier.- 96.29%

2. NeighborsClassifier- 97.29%

3. XGBClassifier- 98.70%**

For the dataset email me :

islamoahidul12@gmail.com