As the semester develops links to additional course resources will be placed here.

- Tutorial examples up through lecture 5. This zip files contains seven early tutorials. These include Tutorial 4 which illustrates how to read sucessive frames from an mpege video.

- Tomáš Bořil Fourier Series 3D. This site lets you control the construction of different functions by manipulating the phase and magnitude of constiuent parts of the signal. The visualization takes advanatage of a 3D view that is clever and allows more information be shown in a single presentation.
- Evan Wallace's interactive DFT Demo. Evan Wallace has built a very nice interactive site to experiment with the Discrete Fourier Transform. The demo includes the ability through simple mouse over moves to low pass filter a signal.
- Dave Watts Ejectamenta Fourier Site. Dave Watts has built an excellent 2D fourier transform visualization tool that allows one to move backward and forward between the spatial domain, e.i. a greyscale image, and the Frequency domain. For testing I prefer the following image of the CSU Oval. Pay attention to the Short Instructions and in particular the guideance on how to construct a low pass and a high pass filter. Also, if you want to test your skill, supress the 'noise' consisting of a sinusoidal disturbance in this image of the letter B.

- Dan
Aloni has developed a nice tutorial and working example of how
backpropogation works on the MNIST dataset. Ben Sattleberg here at
CSU made some modifications to make the example work more smoothly
with the
`dataset.py`

library. You can download this local version here at aloni_backprop.zip

- Jason Brownlee's MNIST Keras Tutorial is an excellent introduction to the simplicity of specifiying and training networks using the Keras interface. Keep in mind how much is hidden from the user with this level of abstraction in the code, and then enjoy the compact and relatively clear specifications provided in the examples. For convenience this zipped folder has the first two examples from Brownlee's tutorial readdy to unpack and run.

- Matt Dragon, our guest lecturer for April 22, is making cs510-inception-demo.tar available before lecture so that all students, or at a minimum all student teams, can have this code downloaded on a laptop and ready to begin working with in adviance of lecture on Monday April 22.

- There are a variety of ways to utilze TensorBoard to inspect different aspects of a network during test and training. Source code for the mnist_with_summaries.py is availble on GitHub. We will review this example in Class on April 26.