Lecture 14 of 47Week 3 : Forms of Representation
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Prof. Carl Gustaf Jansson · KTH Royal Institute of Technology, Sweden
Credits and licence
- From
- Machine Learning, ML, KTH Royal Institute of Technology, Sweden (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
- Who can watch
- Tweens profiles and older. How courses are placed
All the lectures
- Introduction to the Machine Learning Course
- Foundation of Artificial Intelligence and Machine Learning
- Intelligent Autonomous Systems and Artificial Intelligence
- Applications of Machine Learning
- Characterization of Learning Problems
- Objects, Categories and Features
- Feature related issues
- Scenarios for Concept Learning
- Forms of Representation
- Decision Trees
- Bayes (ian) Belief Networks
- Artificial Neural Networks
- Genetic algorithm
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- Inductive Learning based on Symbolic Representations and Weak Theories
- Generalization as Search - Part 01
- Generalization as Search - Part 02
- Decision Tree Learning Algorithms - Part 01
- Decision Tree Learning Algorithms - Part 02
- Instance Based Learning - Part 01
- Instance Based Learning - Part 02
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- Machine Learning enabled by Prior Theories
- Explanation Based Learning
- Inductive Logic Programming
- Reinforcement Learning - Part 01 Introduction
- Reinforcement Learning - Part 02 Learning Algorithms
- Reinforcement Learning - Part 03 Q - Learning
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- Fundamentals of Artificial Neural Networks - Part1
- Fundamentals of Artificial Neural Networks - Part2
- Perceptrons
- Model of Neuron in an ANN
- Learning in a Feed Forward Multiple Layer ANN - Backpropagation
- Recurrent Neural Networks
- Hebbian Learning and Associative Memory
- Hopfield Networks and Boltzman Machines - Part 1
- Hopfield Networks and Boltzman Machines - Part 2
- Convolutional Neural Networks - Part 1
- Convolutional Neural Networks - Part 2
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- Tools and Resources
- Interdisciplinary Inspiration
- Lecture 8.2 - Introduction to a Systematic Example
- ML Course Week 8.3
- Live Session 24-02-2021
- Live Session 06-04-2021