*[Practical Deep Learning For Coders, Part 1](https://course.fast.ai/) from [Fast.ai](https://fast.ai/)

*[Introduction to Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/)(ISL)[[pdf]](http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf) (The famous text, [Elements of Statistical Learning](https://web.stanford.edu/~hastie/ElemStatLearn/), by the same authors is also fantastic, but requires significantly more math/stat preliminaries.)

* Dr. Gentle's (GMU) Spring 2015 [CSI 772](http://mason.gmu.edu/~jgentle/csi772/15s/) syllabus.

## Curriculum

...

...

@@ -55,12 +56,14 @@ The following give a survey (high-level overview of developments in the field) o

* Three Giants' Survey: [Deep learning](http://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf); LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton (2015).

* Deep Learning 2018 [Lesson 1: Recognizing Cats and Dogs](https://course.fast.ai/lessons/lesson1.html)

This chapter in ISL introduces R and the concept of statistical learning and some _very important concepts_ for assessing model accuracy.

* Introduction to Statistical Learning: Chapter 2 [[pdf]](http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf)

* Exercises 3.1, 3.2, 3.3, and 3.8.

### Week 2

...

...

@@ -80,6 +83,7 @@ These papers discuss two key topics: how data is collected and how to work on a

The following paper follow the "eve" of deep learning when deep learning showed promise and began to take off. The Fast.ai video introduces the Convolutional Neural Network (CNN) which was a milestone in deep learning.

* Deep Learning 2018 [Lesson 2: Convolutional Neural Networks](https://course.fast.ai/lessons/lesson2.html)

*[A fast learning algorithm for deep belief nets](http://www.cs.toronto.edu/~hinton/absps/ncfast.pdf); Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh (2006).

*[Reducing the dimensionality of data with neural networks](http://www.cs.toronto.edu/~hinton/science.pdf); Hinton, Geoffrey E., and Ruslan R. Salakhutdinov (2006).

...

...

@@ -88,6 +92,7 @@ The following paper follow the "eve" of deep learning when deep learning showed

This chapter of ISL introduces regressions, a tool for finding relationships between two or more numerical data.

* Introduction to Statistical Learning: Chapter 3 [[pdf]](http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf)