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Stanford University

Deep Learning - Class Introduction and Logistics - Lecture 1

Stanford University via YouTube

Overview

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Explore the foundations of deep learning in this comprehensive lecture from Stanford University's CS230 course. Delve into why deep learning is gaining prominence, understand essential AI tools, and grasp the course's objectives. Learn about Machine Learning Yearning and gain insights into the differences between machine learning and deep learning. Discover how AI applications vary between traditional businesses and internet companies, and understand the contrast between Agile and Waterfall methodologies. Get guidance on course selection, explore the common sequence of AI-related classes, and hear about meaningful successes in the field. Familiarize yourself with the course format, structure, and daily life, including grading formulas and programming assignments. Witness demonstrations of object detection and learn about various project opportunities in this informative session led by Andrew Ng and Kian Katanforoosh.

Syllabus

Intro
Why is deep learning taking off
Tools of AI
Course Goals
Machine Learning Yearning
Class Overview
Machine Learning Deep Learning AI
Shopping Mall vs Internet Company
Agile vs Waterfall
Which classes should you take
Machine Learning vs CS230
Common Sequence
Most Meaningful Successes
Course Format
Course Structure
Course Life
Multimeter
Grading formula
Programming assignments
Object detection
Demonstration
Other Projects

Taught by

Stanford Online

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