Machine Learning from Zero

Machine Learning from Zero: Build Your First Models in Python

Have you ever wondered how computers predict results, estimate prices, or classify data?

Learn the fundamentals of Machine Learning through beginner-friendly explanations, Python demonstrations, simple diagrams, and practical exercises.

What You'll Learn

• Understand Machine Learning and its basic workflow.

• Work with datasets, features, targets, and train/test splits.

• Explore data using Pandas and NumPy.

• Understand Regression and Classification.

• Build a Linear Regression model.

• Learn Logistic Regression and K-Nearest Neighbors (KNN).

• Explore Decision Trees and Random Forests.

• Evaluate models using appropriate performance metrics.

• Build a student Pass/Fail prediction project.

Who Is This Course For?

Students, aspiring developers, and beginners who want to start learning Machine Learning through practical Python examples.

Requirements

• Basic Python knowledge is helpful.

• A computer and internet connection.

• Access to Google Colab to run the coding exercises.

No previous Machine Learning experience is required.

How the Course Works

Learn concepts step by step, study code examples, complete practical exercises, and apply your knowledge in a mini-project.

The focus is on understanding how the algorithms work, why we use them, and how to evaluate their predictions.

Instructor: Pravin Kumar M
Level: Beginner
Language: English
Format: Self-paced lessons and practical coding exercises

This is an introductory educational course. It does not promise job placement, advanced expertise, or professional certification.