Unveiling Customer Secrets: 5 ML Models in Action | Olist Brazil Dataset Project (Part 2)

Описание: 🔍 Unveiling Customer Secrets: 5 ML Models in Action | Olist Brazil Dataset Project (Part 2)

In this video, we dive deep into model building using the popular Olist E-commerce dataset from Brazil. Our goal? To uncover patterns in customer behavior and predict outcomes like satisfaction or delivery success using five top machine learning models:

✅ Random Forest
✅ LinearSVC
✅ Logistic Regression
✅ XGBoost
✅ AdaBoost

We compare each model's accuracy, explain how they work, and help you understand when to use which model in real-world projects.

📊 Whether you're a beginner or looking to enhance your ML portfolio, this is a great hands-on project to follow!

💡 What You’ll Learn:
How different ML models perform on the same dataset

Practical model interpretation and selection

E-commerce-specific feature engineering insights

📁 Dataset: Olist Brazil E-Commerce Public Dataset
📌 This is Part 2 of a full project series:

Part 1: Data Cleaning & EDA

Part 2: Model Building & Accuracy Comparison https://colab.research.google.com/dri...

Part 3: Model Evaluation & Deployment (Coming Soon!)

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💬 Got questions or want the code? Drop a comment below!

#MachineLearning #OlistDataset #RandomForest #XGBoost #ModelComparison #EcommerceAI #PythonProjects #CustomerSatisfaction