Intro to Deep Learning - ML Tech Talks
Offered By: TensorFlow via YouTube
Course Description
Overview
Syllabus
- Intro and outline
- TensorFlow.js demos + discussion
- AI vs ML vs DL
- What’s representation learning?
- A cartoon neural network more on this later
- What features does a network see?
- The “deep” in “deep learning”
- Why tree-based models are still important
- How your workflow changes with DL
- A couple illustrative code examples
- What’s a hyperparameter?
- The skills that are important in ML
- An example of applied work in healthcare
- Families of neural networks + applications
- Encoder-decoders + more on representation learning
- Families of neural networks continued
- Are neural networks opaque?
- Building up from a neuron to a neural network
- A demo of representation learning in TF Playground
- Importance of activation functions
- What’s a neural network library?
- Overfitting and underfitting
- Autoencoders and anomaly detection screencast and demo
- Book recommendations
Taught by
TensorFlow
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