Unsupervised Learning, Recommenders, Reinforcement Learning by Naiyan Noor.pdf

Machine learning is a branch of artificial intelligence (AI) where computers learn patterns from data and make predictions or decisions without being explicitly programmed. Instead of following fixed rules, a machine learning system improves its performance by analyzing examples and experience.

Key points:

Data-driven: Learns from past data.

Prediction: Can forecast outcomes (like sales or weather).

Automation: Reduces need for manual programming.

Types:

Supervised Learning: Learns from labeled data.

Unsupervised Learning: Finds patterns in unlabeled data.

Reinforcement Learning: Learns by trial and error using feedback.

In short, machine learning lets computers “learn” and make smarter decisions over time.

1. Mar 4, 2024
Naiyan Noor
Unsupervised Learning, Recommenders,
Reinforcement Learning
an online non-credit course authorized by DeepLearning.AI and Stanford University and
offered through Coursera
has successfully completed
Andrew Ng
Founder, DeepLearning.AI and Adjunct Professor, Stanford University
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