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1
Introduction
2
Steps of an ML project
3
Voiceactivated devices
4
How to select a project
5
Visualization
6
Millennials
7
Feasibility
8
Network problem
9
Discussion
Description:
Dive into a comprehensive lecture on full-cycle deep learning projects delivered by Andrew Ng and Kian Katanforoosh at Stanford University. Explore the essential steps of machine learning projects, focusing on voice-activated devices as a case study. Learn how to select an appropriate project, utilize visualization techniques, and address the unique challenges faced by millennials in the field. Gain insights into assessing project feasibility and tackling network problems. Engage with the discussion on various aspects of deep learning project development and management. Follow along with the course schedule and access additional resources through the provided Stanford CS230 website.

Deep Learning Full-Cycle Projects - Lecture 3

Stanford University
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