Multiple Linear Regression Explained with Example | Beginner’s Guide to Multiple Linear Regression

Описание: 🎓 Welcome to the Ultimate MLOps Course 2025 – Your step-by-step guide to deploying machine learning models the right way using MLflow, Docker, Kubernetes, Kubeflow, and CI/CD pipelines.

In this course, you'll get a complete overview of the course structure, what you'll learn, the tools we'll use, and how this course will turn you from a data scientist to an MLOps engineer ready for production environments.

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🧠 📊 Multiple Linear Regression Explained with Example | Beginner’s Guide
Multiple Linear Regression is a powerful machine learning algorithm used when you want to predict an outcome based on two or more input features. It's an essential step beyond simple linear regression and is widely used in real-world applications like finance, marketing, and healthcare.

In this beginner-friendly video, you'll learn:

What Multiple Linear Regression is

How it works

When to use it

A hands-on example to see it in action

Whether you're new to machine learning or reviewing the basics, this video will give you a clear and practical understanding of how multiple linear regression works.

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📚 What You'll Learn in This MLOps Course:
✅ MLOps concepts from beginner to advanced
✅ ML experiment tracking & version control using MLflow
✅ CI/CD pipelines using GitHub Actions for ML models
✅ Containerization of ML applications using Docker
✅ Model deployment on Kubernetes with real-world use cases
✅ Introduction to Kubeflow and building Kubeflow Pipelines
✅ Model monitoring, security, logging, and versioning
✅ Scalable production-ready model serving
✅ A full end-to-end deployment case study

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🛠 Technologies You Will Master:
Python & SkLearn
Git & GitHub Actions
MLflow (Experiment Tracking + Model Registry)
Docker (Containerization)
Kubernetes (Orchestration)
Kubeflow (Automation)
Prometheus, Grafana (Monitoring)

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IMPORTANT LINKS:
🔗 Full Course Playlist:    • MLOps Course 2025: From Model to Production  


📁GitHub Code Repo: https://github.com/edquestofficial/ml...
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🎯 Who Is This Course For?
Data Scientists & ML Engineers
Backend Developers exploring AI/ML
Students preparing for AI/ML DevOps roles
Anyone building production-ready ML systems

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📆 Course Schedule:
This course is divided into 15 structured modules, released every day on this channel. Make sure you subscribe and turn on notifications 🔔 to follow along in real-time.

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