<jupyter_start><jupyter_text>Chapter 1My notes on Chapter 1 of the [fast.ai](https://www.fast.ai) course [Deep Learning for Coders](https://course.fast.ai). Chapter notes* Classification vs Regression: Classification allocates predicted values to discrete classes or categories like `cat` or `dog`; regression predicts numeric quantities like temperature or location.  End of Chapter Questions1. Name 5 areas where deep learning is now the best tool in the world    Book page 3:    - Lots of math False    - Lots of data False    - Lots of expensive computers False    - A PhD False (page 10)1. Name five areas where deep learning is now the best in the world.    Book page 4:    - Natural Language Processing    - Computer Vision    - Image generation    - Financial forecasting    - Protein folding1. What was the name of the first device that was based on the principle of the artificial neuron?    Book page 5: the <NAME>1. Based on the book of the same name, what are the requirements for parallel distributed processing (PDP)?    Book page 6:    - A set of processing units     - A state of activation    - An output function for each unit    - A pattern of connectivity among units    - A propagation rule for propagating patterns of activities through the network of connectivities    - A learning rule whereby patterns of connectivity are modified by experience    - An environment within which the system must operate1. What were the two theoretical misunderstandings that held back the field of neural networks?    Page 6/7:    - single layer of neurons not sufficient for even simple functions like XOR    - lack of computing power meant networks with >2 layers were too big and slow to be useful (is this really a *theoretical* limitation?)1. What is a GPU?    Page 14:    - a graphical processing unit.  1. Open a notebook and execute a cell containing: `1+1`. What happens?<jupyter_code>1+1<jupyter_output><empty_output>
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