Page 22 - AI & Machine Learning for Beginners: A Guided Workbook

Data: The Key to AI’s Future

Unlike expert systems, machine learning (ML) offered a new
approach—instead of relying on predefined rules, ML algorithms
learned patterns directly from data. This shift was fueled by the
rapid growth of digital information, making machine learning
(ML) techniques far more practical and scalable.

Key ML Algorithms Developed in the 1990s

Support Vector Machines (SVMs): A powerful tool for

classification tasks, used in text and image recognition.
Decision Trees & Random Forests: Flexible models for

structured decision-making, applied in finance and healthcare.
Hidden Markov Models (HMMs): Advanced speech

recognition techniques, leading to voice-based AI breakthroughs.
As ML gained momentum, AI research rebounded, setting the
stage for deep learning and the AI explosion of the 2000s.

The Data Explosion & Deep Learning Revolution (2000s -
Present)

The 2000s ushered in a new era of AI, driven by two game-
changing developments:

Big Data: The internet, smartphones, and digital services

generated massive amounts of data, fueling AI systems to learn
and improve.

Advancements in Computing: The rise of Graphics

Processing Units (GPUs) accelerated AI model training, making
deep learning feasible.

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