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All Programs
Computers
Artificial Intelligence
Considering Deep Learning Basics
Considering Deep Learning Basics
Curriculum
7 Sections
23 Lessons
10 Weeks
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Chapter 5: Reviewing Matrix Math and Optimization
3
1.1
Revealing the Math You Really Need
1.2
Understanding Scalar, Vector, and Matrix Operations
1.3
Interpreting Learning as Optimization
Chapter 6: Laying Linear Regression Foundations
5
2.1
Combining Variables
2.2
Mixing Variable Types
2.3
Switching to Probabilities
2.4
Guessing the Right Features
2.5
Learning One Example at a Time
Chapter 7: Introducing Neural Networks
3
3.1
Discovering the Incredible Perceptron
3.2
Hitting Complexity with Neural Networks
3.3
Struggling with Overfitting
Chapter 8: Building a Basic Neural Network
2
4.1
Understanding Neural Networks
4.2
Looking Under the Hood of Neural Networks
Chapter 9: Moving to Deep Learning
5
5.1
Seeing Data Everywhere
5.2
Discovering the Benefits of Additional Data
5.3
Improving Processing Speed
5.4
Explaining Deep Learning Differences from Other Forms of AI
5.5
Finding Even Smarter Solutions
Chapter 10: Explaining Convolutional Neural Networks
3
6.1
Beginning the CNN Tour with Character Recognition
6.2
Explaining How Convolutions Work
6.3
Detecting Edges and Shapes from Images
Chapter 11: Introducing Recurrent Neural Networks
2
7.1
Introducing Recurrent Networks
7.2
Explaining Long Short-Term Memory
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