Portfolio Project: Microsoft Malware Detection Project

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Section 1: Overview

  1. Course Overview
  2. How to Get Queries Resolved
  3. Download Resources
  4. Problem Description

Section 2: Setup new environment

  1. Python Setup - Local Installation
  2. Python Setup - Google Colab

Section 3: Understanding the data

  1. Data Overview
  2. Optimize Memory Usage
  3. Understand The Data
  4. Course Review

Section 4: Preprocess the data

  1. Data Preprocessing for EDA

Section 5: Perform EDA ( Exploratory Data Analysis)

  1. Need for EDA
  2. Exploratory Data Analysis Part 1
  3. Exploratory Data Analysis Part 2
  4. Course Review

Section 6: Statistical Significance Tests

  1. Chi Squared Test Theory and Maths
  2. Chi Square Test and Odds Ratio Demo
  3. ANOVA Concept- Intuition 4 ANOVA maths
  4. ANOVA Demo

Section 7: Engineer new features and process data

  1. Feature Engineering - Domain Specific
  2. Feature Encoding Approaches
  3. Feature Encoding Demo
  4. Data Processing for Model Building
  5. Course Review

Section 8: Evaluation methods for classificatio

  1. Confusion Matrix and Evaluation Metrics
  2. Concordance and Discordance
  3. ROC Curve
  4. Precision Recall Curve
  5. Evaluation Metrics Demo
  6. Capture Rates and Gains

Section 9: Machine Learning Models

  1. Decision Trees and Improvements
  2. Random Forests
  3. XGBoost
  4. LightGBM
  5. Course Review

Section 10: Model improvement and interpretation

  1. Tuning Hyperparameters
  2. Feature Importance
  3. Feature Importance Demo

Section 11: Summary

  1. Final Words
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