Add ISL exercises for Week 1 and Week 2

parent 74f7e432
......@@ -32,6 +32,7 @@ Almost all of the material has come from the following sources:
* [Deep Learning Papers Reading Roadmap](
* [Practical Deep Learning For Coders, Part 1]( from [](
* [Introduction to Statistical Learning]( (ISL) [[pdf]]( (The famous text, [Elements of Statistical Learning](, by the same authors is also fantastic, but requires significantly more math/stat preliminaries.)
* Dr. Gentle's (GMU) Spring 2015 [CSI 772]( 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](; LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton (2015).
* Deep Learning 2018 [Lesson 1: Recognizing Cats and Dogs](
* [Lesson 1 wiki](
#### Statistical Learning
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]](
* 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 video introduces the Convolutional Neural Network (CNN) which was a milestone in deep learning.
* Deep Learning 2018 [Lesson 2: Convolutional Neural Networks](
* [Lesson 2 wiki](
* [A fast learning algorithm for deep belief nets](; Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh (2006).
* [Reducing the dimensionality of data with neural networks](; 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]](
* Exercises 3.5, 3.7, 3.9, and 3.14.
### Future Weeks
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