#Prepare Dataset Challenge
#Overview
This is the code for this video by Siraj on Youtube. The brainscan dataset is entirely fictional, but serves as a good example on how to prepare a dataset. Real examples do exist but, too many features to sift through for a short video.
##Dependencies
- tensorflow (https://www.tensorflow.org/get_started/os_setup)
- numpy (pip install numpy)
##Demo
Run the following in terminal
$ python softmax.py --train simdata/linear_data_train.csv --test simdata/linear_data_eval.csv --num_epochs 5 --verbose True
Add your own test data to test the model out.
##Challenge The challenge for this video is to create a pokemon classifier by their type 1 (i.e fire, water, grass, etc.) using this pokemon dataset on Kaggle. It will be great practice in data preparation (feature selection, cleaning, etc.) Post your github link in the comments and i'll announce the winner in the next video. Due date is December 22nd at Noon PST.
##Credits
Credits go to Jason Baldridge. I've merely created a wrapper to get people started.