Machine Learning (ML) is a branch of Artificial Intelligence that enables computers to learn from data and improve their performance without being explicitly programmed. Instead of following fixed instructions, ML systems identify patterns in data and make predictions or decisions.

ML is widely used in applications such as recommendation systems, image recognition, speech processing, fraud detection, and predictive analytics. With the growth of data and computing power, machine learning has become a core technology in modern software systems.

Key topics you will learn in this course:

1. Introduction to Machine Learning

2: Python for Machine Learning

3: Data Preprocessing

4: Statistics & Probability

5: Supervised Learning

6: Unsupervised Learning

7: Model Optimization

8: Advanced Algorithms

9: Deep Learning Basics

10: Natural Language Processing (NLP)

11: Computer Vision Basics

12: Model Deployment

13: Real-World Projects