Neural Networks

Machine Learning    |    Beginner
  • 13 Videos | 30m 56s
  • Includes Assessment
  • Earns a Badge
Likes 63 Likes 63
Due to recent advancements in processing, neural networks have become easier to train, which made them extremely popular. Explore neural networks and how to use them.

WHAT YOU WILL LEARN

  • describe neural networks and their capabilities
    describe how different neural networks are structured
    describe how cost functions are used to train neural networks
    describe activation functions and list different types of commonly used activation functions
    describe feedforward neural networks and the intuition behind calculating gradients in neural networks
    describe how to use backpropagation for more efficient neural network training
    describe batch learning and why it makes neural network training easier
  • describe TensorFlow and its high-level architecture
    set up TensorFlow for use on a CPU
    import data into TensorFlow using built-in data sources and external data sources
    implement and train a single-layer NN in TF
    implement and train a multilayer NN in TF
    use TensorFlow to create a NN that predict home prices

IN THIS COURSE

  • Playable
    1. 
    Introducing Neural Networks
    2m
    UP NEXT
  • Playable
    2. 
    Neural Network Structures
    2m 34s
  • Locked
    3. 
    Cost Functions for Neural Networks
    2m 29s
  • Locked
    4. 
    Activation Functions
    1m 55s
  • Locked
    5. 
    Training Neural Networks
    2m 53s
  • Locked
    6. 
    Training Neural Networks With Backpropagation
    1m 32s
  • Locked
    7. 
    Batch Learning
    1m 23s
  • Locked
    8. 
    Introducing TensorFlow
    1m 33s
  • Locked
    9. 
    Setting Up TensorFlow
    2m 52s
  • Locked
    10. 
    Importing Data in TensorFlow
    4m 36s
  • Locked
    11. 
    Building and Training a Single Layer NN in TF
    2m 58s
  • Locked
    12. 
    Building and Training a Multilayer NN in TF
    1m 50s
  • Locked
    13. 
    Exercise: Predict Home Prices with a NN
    2m 24s

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