DP:700 Bank Customer Churn Using Synapse Data Science in Microsoft Fabric | Full Tutorial

Welcome to this comprehensive tutorial on Synapse Data Science workflows in Microsoft Fabric! 🚀 In this video, we walk you through an end-to-end machine learning project where we build a model to predict bank customer churn—the rate at which customers leave the bank.

Whether you're a data science enthusiast or a professional looking to enhance your skills with Microsoft Fabric, this tutorial covers everything you need to know!

🛠️ What You’ll Learn:
Installing Custom Libraries 📦
Loading & Preprocessing Data 🗂️
Exploratory Data Analysis (EDA) using Fabric Data Wrangler 🔍
Building Machine Learning Models with scikit-learn & LightGBM 🤖
Experiment Tracking with MLflow and Fabric Autologging 📝
Model Evaluation & Saving 🏆
Visualizing Results in Power BI 📊

00:00 – Introduction
01:45 – Installing Custom Libraries
03:30 – Loading the Data
06:15 – Exploratory Data Analysis (EDA)
10:45 – Data Wrangling with Fabric Data Wrangler
15:20 – Building ML Models with scikit-learn & LightGBM
20:00 – Tracking Experiments using MLflow & Fabric Autologging
25:10 – Evaluating & Saving the Final Model
28:45 – Power BI Visualizations for Model Performance
32:00 – Conclusion & Next Steps


📂 Resources & Links:
🔗 Download the Dataset
🔗 Microsoft Fabric Documentation
🔗 scikit-learn Official Site
🔗 LightGBM Documentation
🔗 Power BI Tutorials