Bridging Privacy and Learning: Differential Privacy and Federated Learning in Python
Created by Team Mammoth
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24 lectures
01
Skill level
All levels
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Sections
3
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Lectures
24
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Instructor
Team Mammoth
What's inside
This course includes.
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3
Sections
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Certificate of completion
Included
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Mobile and desktop access
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AI learning assistance
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Course content
Curriculum & lectures.
+ Differential Privacy Project 9 lectures
02 Build An Initial Database
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00 What Is Differential Privacy
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01 Differential Privacy Project Introduction
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03 Build A Parallel Database
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04 Build Multiple Parallel Databases
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05 Determine If Query Leaks Private Data
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06 Calculate Sensitivity Of Mean Query
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07 Build Local Differential Privacy
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01 Source Files
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+ Deep Learning Differential Privacy Project 5 lectures
01 Build Database
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02 Build A Differential Privacy Query
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00 Deep Learning Differential Privacy Introduction
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03 Perform Pate Analysis
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02 Source Files
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+ Build a Federated Learning Model 10 lectures
00 What Is Federated Learning
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01 Generate A Dataset
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02 Build A Regular Model
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05 Build An Aggregator Model
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04 Build A Client-Side Model
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03 Visualize Model Results
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08 Evaluate The Model
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06 Generate Clients Dataset
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07 Execute The Federated Learning Model
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03 Source Files
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Instructors
Taught by people who ship.
Team Mammoth
Instructor
Produced by a team of Mammoth Club industry experts. Over 14 years, Mammoth Club has built a global student community in 190+ countries with 9+ million courses sold, releasing over 1,000+ courses and 5,000+ hours of video content.
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