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Curriculum

    1. What even is ML?

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    2. Types of Models (By Learning Paradigm)

    3. Classical ML Models

    4. What is Deep Learning?

    5. Summary: Classical ML Models vs. Deep Learning Models

    6. Regression (Linear and Logistic)

    7. Classification

    8. Quiz: Intro to ML

    1. Convolutional Neural Networks

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    2. ResNet

    3. Recurrent Neural Networks (RNNs)

    4. Long Short-Term Memory Networks (LSTMs)

    5. Quiz: Types of Neural Nets

    1. Recommendation Systems

    2. Quiz: Recommendation Systems

    1. When ML is not needed

    2. Quiz: When ML is not needed

    1. The Training Loop

    2. Backpropagation and Optimizers

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    3. Train/Test Split

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    4. Common Train/Test Splits

    5. Validation Set

    6. Quiz: Model Development (Big Picture)

    1. Regression Loss Functions

    2. Classification Loss Functions

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    3. Quiz: Loss Functions

Highlights

  • 12.5 hours of video content
  • Over 500 practice questions
  • Pass guarantee
  • 3 purchasing options

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