Difference between revisions of "Watch me Build a Cybersecurity Startup"

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** [[Watch me Build a Retail Startup]] | Siraj Raval  
 
** [[Watch me Build a Retail Startup]] | Siraj Raval  
 
** [[Watch me Build a Trading Bot]] | Siraj Raval
 
** [[Watch me Build a Trading Bot]] | Siraj Raval
 +
  
 
* [http://aws-web-analytics-dashboard.s3-website-us-east-1.amazonaws.com/ Demo]
 
* [http://aws-web-analytics-dashboard.s3-website-us-east-1.amazonaws.com/ Demo]
 
* [http://github.com/llSourcell/Build-a-Cybersecurity-Startup/tree/master/analytics-dashboard Analytics Dashboard React Application]
 
* [http://github.com/llSourcell/Build-a-Cybersecurity-Startup/tree/master/analytics-dashboard Analytics Dashboard React Application]
 
* [http://reactjs.org/ React] =  JavaScript library for building user interfaces
 
* [http://reactjs.org/ React] =  JavaScript library for building user interfaces
* [https://github.com/facebook/create-react-app Create React App | GitHub]
+
* [http://github.com/facebook/create-react-app Create React App | GitHub]
 +
* [[Python#Flask |Flask]] microframework for Python
  
 
== DharmaSecurity ==
 
== DharmaSecurity ==

Revision as of 23:40, 1 September 2019

YouTube search... ...Google search


DharmaSecurity

I've built a demo app called DharmaSecurity, a fraud detection tool for businesses. The way it works is that once signed up, a business will paste a code snippet into their website, and then they'll get access to a dashboard that tells them how many fraudulent accounts they have. Our app will use machine learning to automatically remove suspected fraud accounts, and flag likely ones for review. To build this, I use a suite of AWS tools, python, javascript, a logistic regression model, a credit card fraud dataset, and a library called openmined to enable federated learning and secure multiparty computation. I've packed a lot into this video, animations, code, music, screencasts, skits, etc. Enjoy! Code for "a Cybersecurity Startup" | Siraj Raval - GitHub