# Introduction to Deep Learning
## Slides
* Logisitic, software and linear algebra lecture in
[keynote](../../slides/1_22/1-Logistics.key),
[PDF](../../slides/1_22/1-Logistics.pdf)
* Jupyter notebooks
* Linear Algebra in [Jupyter](../../slides/1_22/linear-algebra.ipynb),
[PDF](../../slides/1_22/linear-algebra.pdf)
* NDArray in [Jupyter](../../slides/1_22/ndarray.ipynb),
[PDF](../../slides/1_22/ndarray.pdf)
## Homework 1
[Jupyter](../../homeworks/homework1.ipynb) and
[PDF](../../homeworks/homework1.pdf). Note that the PDF version is just
there to allow you to render it easily on a viewer. For homework
submission you will need to use Jupyter.
## Extended Reading
* [Introduction to Deep Learning](https://d2l.ai/chapter_introduction/index.html)
* [Installation](https://d2l.ai/chapter_installation/index.html)
* [Linear Algebra](https://d2l.ai/chapter_preliminaries/linear-algebra.html)
* [Using Jupyter Notebook](https://d2l.ai/chapter_appendix-tools-for-deep-learning/jupyter.html)
* [Using AWS to Run Code](https://d2l.ai/chapter_appendix-tools-for-deep-learning/aws.html)
## Videos