Machine Learning
Artificial Intelligence
14 Videos | 47m 12s - Includes Assessment
- Earns a Badge
Sometimes agents must learn how to associate certain conditions with actions and outcomes. Explore the principles of machine learning and how to use it to make smarter agents.
WHAT YOU WILL LEARN
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describe how AI learns and the different types of machine learning
describe how examples can be used for learning
describe decision trees and how the model expresses knowledge
describe entropy and information gain for learning decision tree models
describe how to choose attributes to learn a decision tree
describe overfitting and how decision tree models can be made to mitigate this issue
describe neural networks and how they apply to artificial intelligence -
describe the structure of a neural network and its individual neurons
list some of the common types of neural networks and what problems they might be good at solving
describe how machine learning works with a perceptron
describe how perceptron learning can be generalized to a multilayered neural network
describe convolutional neural networks
describe recurrent neural networks
describe how a perceptron can learn how to achieve a particular result given a set of examples
IN THIS COURSE
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1.How Computers Can Learn3m 31sUP NEXT
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2.Learning From Examples3m 2s
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3.Using Decision Trees1m 19s
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4.Decision Tree Learning: Information Gain2m 5s
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5.Decision Tree Learning: Choosing Attributes4m 43s
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6.Overfitting2m 23s
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7.Artificial Neural Networks2m 43s
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8.Neural Network Structure2m 19s
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9.Types of Neural Networks4m 19s
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10.Perceptron Learning1m 24s
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11.Deep Neural Networks3m 43s
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12.Convolutional Neural Networks3m 15s
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13.Recurrent Neural Networks3m 53s
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14.Exercise: Make a Perceptron Learn From Examples2m 2s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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