Introduction to Machine Learning

Fall 2025 • American University of Beirut

Introduction to Machine Learning - Resources & References

This is a comprehensive collection of external learning materials, datasets, tools, and references.

Core Course Materials

Essential Textbooks (Free Online)

Main Online Courses (in addition to course lectures)

Python Programming Resources

Datasets for Learning and Projects

Lebanese Data Sources

General Machine Learning Datasets

Scientific and Research Data

Economics and Social Data

Specialized Domains

Course-Specific Practice Datasets

For Linear Regression & Statistics

For Classification

For Time Series

Programming Tools & Libraries

Core Python Libraries

# Data Science Stack
import numpy as np           # Numerical computing
import pandas as pd          # Data manipulation
import matplotlib.pyplot as plt  # Basic plotting
import seaborn as sns        # Statistical visualization
import scipy as sp           # Scientific computing

# Machine Learning
import sklearn               # Classical machine learning
import torch                 # PyTorch deep learning
import tensorflow as tf      # TensorFlow/Keras

Development Environment

Specialized ML Tools

Mathematical Foundations

Linear Algebra Resources

Statistics and Probability

Calculus for ML

Video Learning Resources

Essential YouTube Channels

Lecture Series

Staying Current

Academic Sources

Practice and Competitions

Coding Practice

ML Competitions

Project Ideas

Career Resources

Portfolio Building

Interview Preparation

Community and Support

Online Communities

Quick Reference Sheets

Python Cheat Sheets

ML Algorithm Selection

Scientific Machine Learning

Physics-Informed ML

Research Papers

Topic-Specific Deep Learning Resources

Deep Learning Fundamentals

Advanced Architectures

Time Series and Sequences

Transformers and Language Models

This resource list is continuously updated. Suggest additions by opening an issue in the course repository or proposing them on Slack.