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

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** [[Simple Storage Service (S3)]] - object storage
 
** [[Simple Storage Service (S3)]] - object storage
 
** [http://aws.amazon.com/glue/ Glue] a fully managed extract, transform, and load (ETL) service to prepare and load data for analytics
 
** [http://aws.amazon.com/glue/ Glue] a fully managed extract, transform, and load (ETL) service to prepare and load data for analytics
 +
*** [http://docs.aws.amazon.com/glue/latest/dg/add-crawler.html Crawlers] to populate the AWS Glue Data Catalog with tables
 
** [http://aws.amazon.com/athena Athena] interactive query service to analyze data in Amazon S3 using standard SQL
 
** [http://aws.amazon.com/athena Athena] interactive query service to analyze data in Amazon S3 using standard SQL
 
** [[AWS with TensorFlow]]
 
** [[AWS with TensorFlow]]

Revision as of 12:50, 2 September 2019

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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 (LR) model, a credit card fraud dataset, and a library called OpenMined to enable federated learning and secure multi-party computation. I've packed a lot into this video, animations, code, music, screencasts, skits, etc. Enjoy! Code for "a Cybersecurity Startup" | Siraj Raval - GitHub