| 1 - Analyzing User Behaviour with Unsupervised Machine Learning & K Means Clustering.mp4 | 86.7 MB | ||
| 1 - Building Intrusion Detection Model with Logistic Regression.mp4 | 93.6 MB | ||
| 1 - Building Intrusion Detection Model with Random Forest Classifier.mp4 | 163.2 MB | ||
| 1 - Cleaning Dataset by Removing Missing Values & Duplicates.mp4 | 29.1 MB | ||
| 1 - Conclusion & Summary.mp4 | 31.6 MB | ||
| 1 - Conducting Exploratory Data Analysis.mp4 | 93.9 MB | ||
| 1 - Detecting Cyber Threat with K Nearest Neighbour.mp4 | 139.9 MB | ||
| 1 - Detecting Cyber Threat with XGBoost.mp4 | 70 MB | ||
| 1 - Detecting Phishing Email with NLP & Naive Bayes.mp4 | 84.6 MB | ||
| 1 - Feature Selection with Random Forest.mp4 | 112.4 MB | ||
| 1 - Finding & Downloading Cyber Security Datasets From Kaggle.mp4 | 64 MB | ||
| 1 - How Intrusion Detection Model Works.mp4 | 50.8 MB | ||
| 1 - HowIntrusionDetectionModelWorks.png | 295.3 KB | ||
| 1 - Introduction.mp4 | 79.4 MB | ||
| 1 - MLandNLPApplicationsinCyberSecurity.png | 199.5 KB | ||
| 1 - Machine Learning & NLP Applications in Cyber Security.mp4 | 28.7 MB | ||
| 1 - Predicting Vulnerability Score with Decision Tree Regressor.mp4 | 50.5 MB | ||
| 1 - Predicting Vulnerability Score with MLP Regressor.mp4 | 142.1 MB | ||
| 1 - Testing Machine Learning Model in Real Time Simulation.mp4 | 133.5 MB | ||
| 1 - Tools, IDE, and Datasets.mp4 | 66.3 MB | ||
| 1 - Uploading Dataset to Google Colab IDE.mp4 | 34.2 MB | ||
| 1 - UserBehaviourAnalytics.csv | 5.8 KB | ||
| 1 - analyzinguserbehaviourwithunsupervisedmachinelearning.py | 1.4 KB | ||
| 1 - buildingintrusiondetectionmodelwithlogisticregression.py | 2.7 KB | ||
| 1 - buildingintrusiondetectionmodelwithrandomforestclassifier.py | 2.6 KB | ||
| 1 - cleaningcybersecuritydataset.py | 819.2 B | ||
| 1 - detectingcyberthreatwithknn.py | 1.8 KB | ||
| 1 - detectingcyberthreatwithxgboost.py | 2 KB | ||
| 1 - detectingphishingemailwithnlp.py | 1.5 KB | ||
| 1 - exploratorydataanalysiscybersecurity.py | 1.8 KB | ||
| 1 - featureselectionwithrandomforest.py | 1.9 KB | ||
| 1 - predictingvulnerabilityscorewithdecisiontreeregressor.py | 2.1 KB | ||
| 1 - predictingvulnerabilityscorewithmlpregressor.py | 2.2 KB | ||
| 1 - testingmachinelearningmodelinrealtimesimulation.py | 3.2 KB | ||
| 2 - Machine Learning and NLP for Cyber Security.pptx | 2.2 MB | ||
| 2 - Table of Contents.mp4 | 51.3 MB | ||
| 3 - Whom This Course is Intended for.mp4 | 36.5 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 39 total files | |||
Building Machine Learning & NLP Models for Cyber Security
https://WebToolTip.com
Published 9/2025
Created by Christ Raharja
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 21 Lectures ( 3h 47m ) | Size: 1.6 GB
Learn how to build intrusion detection model, detect cyber threat, predict vulnerability score, detect phishing email
What you'll learn
Learn how to build intrusion detection model using Random Forest Classifier
Learn how to detect cyber threat using K Nearest Neighbour
Learn how to predict vulnerability score using MLP Regressor
Learn how to detect phishing email using NLP and Naive Bayes
Learn how to build intrusion detection model using Logistic Regression
Learn how to detect cyber threat using XGBoost
Learn how to predict vulnerability score using Decision Tree Regressor
Learn how to analyze user behaviour using unsupervised machine learning and K Means Clustering
Learn how to conduct exploratory data analysis
Learn how to perform features selection using Random Forest
Learn about machine learning and natural language processing applications in cyber security
Learn how intrusion detection models work. This section covers data collection, preprocessing, feature selection, model training, detecting intrusion
Learn how to clean dataset by removing missing values and duplicates
Learn how to test machine learning model in real time simulation
Requirements
No previous experience in machine learning is required
Basic knowledge in Python and cyber security
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