I am partaking in research with my professor Dr. Boxiang Dong at Montclair State University in using deep learning techniques for anomaly detection. This project is to help with that research. What I have done so far is:

• Implement neural nets w/ TensorFlow
• Implement machine learning classifiers

1. Requirements
2. Resources

• Python 3.5 (Python 3.6+ doesn't work that well w/ TensorFlow; Python 3.5 gets the best results)

• Do not use IDLE as a compiler; very slow to download data
  • Use CMD whenever downloading a lot of data
  • VS Code is a great place for editing and writing code; easy to use and has great extensions (i.e. Python by Microsoft)

• https://stackoverflow.com/questions/22258491/read-a-small-random-sample-from-a-big-csv-file-into-a-python-data-frame?lq=1
• https://stackoverflow.com/questions/12190874/pandas-sampling-a-dataframe
• https://stackoverflow.com/questions/52685774/loading-fashion-mnist-data-takes-too-much-time
• https://community.atlassian.com/t5/Bitbucket-questions/How-to-write-a-table-of-contents-in-a-Readme-md/qaq-p/673363

• Markdown Cheatsheet
• Online Markdown Editor
• Switching Python Environments on VS Code
• How to Delete Commit History in Github

• Echo State Networks in Python

• https://www.howtogeek.com/311287/how-to-connect-to-an-ssh-server-from-windows-macos-or-linux/

• sentdex - Deep Learning basics with Python, TensorFlow and Keras