Explore the distinctions between artificial intelligence, machine learning, and deep learning in this comprehensive 31-minute video. Gain insights into various machine learning paradigms, including supervised, unsupervised, and reinforcement learning. Learn when to apply traditional machine learning techniques versus deep neural networks, with a focus on audio applications. Discover the differences between expert systems and machine learning approaches for tasks like onset detection. Understand the advantages of deep learning in feature engineering and end-to-end solutions. Access accompanying code, slides, and additional resources to further enhance your understanding of AI and its subfields.
Overview
Syllabus
Intro
What you'll learn
Artificial intelligence
Machine learning (ML)
ML vs expert system for onset detection
Expert system: Onset detection
ML onset detection: Training
ML onset detection: Inference
ML paradigms
Unsupervised learning
Reinforcement learning
ML algorithms
Neural network (NN)
Deep learning
Traditional ML vs DL: Feature engineering
Traditional ML vs DL: End-to-end
When should you use DL?
DL applications in audio
Takeaway points
What's up next?
Taught by
Valerio Velardo - The Sound of AI
Related Courses
-
AI and Machine Learning Algorithms and Techniques
-
Deep Learning Crash Course for Beginners
4.0 -
Unsupervised Learning, Recommenders, Reinforcement Learning
-
Deep Learning and Reinforcement Learning
3.0 -
Play by Play: Machine Learning Exposed
-
AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning
