## Excerpts

**Simple machine learning**algorithms- Сhoice of
**representation** - How does deep learning solve the
**central problem**in representation learning? - 2 main ways of measuring the
**depth**of a deep learning model **Relationships**between deep learning, representation learning, machine learning, and artificial intelligence- Historical trends in deep learning
- The deep learning’s
**history** **Simple linear models**: predecessors of modern deep learning- Limitations of linear models
- Why has the
**neuroscience**’s role in deep learning been diminished? - What has
**neuroscience**given to deep learning? - What is the «
**computational neuroscience**»? - What is «
**connectionism**»? - What is «
**distributed representation**»? - Deep neural networks in the
**mid-1990s**-**mid-2000s** - The
**third wave**of neural networks research - Increasing
**dataset sizes** - Increasing
**model sizes** - The
**number of connections per neuron**in animals and artificial neural networks - The
**number of neurons**in animals and artificial neural networks - Increasing
**accuracy**,**complexity**and real-world impact