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Mammoth Club All levels 4 sections 27 lectures

Differential Privacy and Federated Learning with Python

01
Skill level
All levels
02
Sections
4
03
Lectures
27
04
Instructor
Team Mammoth
What's inside

This course includes.

4
Sections
27
Lectures
27
Resources
Certificate of completion
Included
Mobile and desktop access
Included
AI learning assistance
Included
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Course content

Curriculum & lectures.

4 sections · 27 lectures
+ 00c Mammoth Interactive Courses Introduction 3 lectures
00 About Mammoth Interactive Locked
01 How To Learn Online Effectively Locked
Source Files Locked
+ 01 Differential Privacy Project 9 lectures
00 What Is Differential Privacy Locked
01 Differential Privacy Project Introduction Locked
02 Build An Initial Database Locked
03 Build A Parallel Database Locked
04 Build Multiple Parallel Databases Locked
05 Determine If Query Leaks Private Data Locked
06 Calculate Sensitivity Of Mean Query Locked
07 Build Local Differential Privacy Locked
Source Files 11 Locked
+ 02 Deep Learning Differential Privacy Project 5 lectures
00 Deep Learning Differential Privacy Introduction Locked
01 Build Database Locked
02 Build A Differential Privacy Query Locked
03 Perform Pate Analysis Locked
Source Files 12 Locked
+ 03 Build a Federated Learning Model 10 lectures
00 What Is Federated Learning Locked
01 Generate A Dataset Locked
02 Build A Regular Model Locked
03 Visualize Model Results Locked
04 Build A Client-Side Model Locked
05 Build An Aggregator Model Locked
06 Generate Clients Dataset Locked
07 Execute The Federated Learning Model Locked
08 Evaluate The Model Locked
Source Files 13 Locked

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