Machine Learning

Welcome to the Machine Learning guide! This README covers essential topics to help you get started with ML.

Topics

1. Introduction to Machine Learning

Learn the basics of Machine Learning, including its definition, significance, and fundamental concepts.

2. Difference Between AI, ML, and DL

Understand the distinctions between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), including their applications and relationships.

3. Types of Machine Learning

Explore the various types of Machine Learning:

Supervised Learning
Unsupervised Learning
Semi-supervised Learning
Reinforcement Learning

4. Online vs. Batch Learning

Discover the differences between Online Learning and Batch Learning, and when to use each method.

5. Instance-Based vs. Model-Based Learning

Dive into Instance-Based Learning and Model-Based Learning, comparing their approaches and use cases.

6. Challenges in Machine Learning

Identify common challenges faced in Machine Learning, including data quality, overfitting, underfitting, and computational requirements.

7. Applications of Machine Learning

Explore various applications of Machine Learning across different fields such as:

Healthcare
Finance
Marketing
Autonomous Vehicles
Natural Language Processing (NLP)

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