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An Introduction to Machine Learning
1. Introduction to Machine Learning
1.1. Projects
1.2. Basic Concepts
1.3. The Python Environment: Anaconda, Colab, and Kaggle
2. Introduction to Python
2.2. Introduction to Python and Basic Syntax
2.3. Built-in Data Types
2.4. Numbers and Strings in Python
2.5. The Boolean Type (
bool
) in Python
2.6. Arithmetic Operators in Python
2.7. Input and Output in Python
2.8. Conditionals and Loops
2.9. Creating Functions in Python
2.10. Essential Built-in Functions in Python
2.11. Packages and Libraries in Python
3. Big Data - Intro Data Engineering using Spark and Hadoop
4. Data Preprocessing
5. Supervised Learning
6. Unsupervised Learning
7. Deep Learning and Neural Networks
8. Computer Vision
9. Natural Language Processing
10. Large Language Models
11. Bibliography
Repository
Open issue
.md
.pdf
Supervised Learning
5.
Supervised Learning
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