Difference between revisions of "Watch me Build a Cybersecurity Startup"
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== [http://aws-web-analytics-dashboard.s3-website-us-east-1.amazonaws.com/ DharmaSecurity] == | == [http://aws-web-analytics-dashboard.s3-website-us-east-1.amazonaws.com/ 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 [[Amazon |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 multiparty computation. I've packed a lot into this video, animations, code, music, screencasts, skits, etc. Enjoy! [https://github.com/llSourcell/Build-a-Cybersecurity-Startup Code for "a Cybersecurity Startup" | Siraj Raval - GitHub] | + | I've built a demo app called [http://aws-web-analytics-dashboard.s3-website-us-east-1.amazonaws.com/ 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 [[Amazon |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 multiparty computation. I've packed a lot into this video, animations, code, music, screencasts, skits, etc. Enjoy! [https://github.com/llSourcell/Build-a-Cybersecurity-Startup Code for "a Cybersecurity Startup" | Siraj Raval - GitHub] |
<youtube>BXw8vQXxvqc</youtube> | <youtube>BXw8vQXxvqc</youtube> | ||
Revision as of 09:42, 2 September 2019
YouTube search... ...Google search
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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 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
