ML workflow using Vertex AI | AutoML | Google Cloud | ML Project | Tutorial | step by step
In this video, I walk through a complete machine learning workflow using Google Vertex AI AutoML to build a predictive model for a real-world problem.
We use the Combined Cycle Power Plant dataset to predict electrical energy output based on environmental factors like temperature, pressure, humidity, and exhaust vacuum. This is a beginner-friendly, step-by-step tutorial covering everything from dataset upload to model training and evaluation.
🚀 What you’ll learn:
How to use Google Vertex AI
Difference between regression and classification
Uploading and preparing tabular datasets
Training a model using AutoML
Evaluating performance (RMSE, R², MAE)
Understanding feature importance
Real-world application of ML in energy systems
📊 Project Overview:
Dataset: Combined Cycle Power Plant
Features: Temperature, Pressure, Humidity, Vacuum
Target: Electrical Power Output (PE)
Model Type: Tabular Regression
Platform: Google Vertex AI AutoML
🔗 Access Google Vertex AI:
https://console.cloud.google.com/vert...
💡 Why this project matters:
This project shows how machine learning can be used to predict energy generation, improve efficiency, and support smarter decision-making in power systems.
🛠 Tools Used:
Google Cloud Platform (GCP)
Vertex AI
AutoML (Tabular)
✨ About Me:
Hi, I’m Ananya — a UX designer exploring AI, machine learning, and human-centered tech.
#MachineLearning #VertexAI #GoogleCloud #AutoML #MLProject #DataScience #AI #Regression #BeginnerFriendly