Introduction to Machine Learning with Python
Get started with Machine Learning in Python. Learn supervised and unsupervised learning with practical code examples.
Machine Learning Fundamentals
Machine Learning is a subset of AI that enables systems to learn and improve from experience. Python has become the go-to language for ML thanks to libraries like scikit-learn, TensorFlow, and PyTorch.
Types of Machine Learning
- Supervised Learning - Learning from labeled data (classification, regression)
- Unsupervised Learning - Finding patterns in unlabeled data (clustering)
- Reinforcement Learning - Learning through rewards and penalties
Your First ML Model
from sklearn.ensemble import RandomForestClassifier
model = RandomForestClassifier(n_estimators=100)
model.fit(X_train, y_train)
predictions = model.predict(X_test)
Getting Started
Start with simple datasets like Iris or MNIST. Understand the basics of data preprocessing, feature engineering, and model evaluation before moving to deep learning.
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