Machine Learning - What Is Easy, Medium, and Hard?
Offered By: Steve Brunton via YouTube
Course Description
Overview
Explore the landscape of machine learning through case studies, examining what tasks are considered easy, medium, and hard in this rapidly advancing field. Gain insights into facial recognition, image classification, and surveillance applications. Delve into more complex areas like image captioning, imitation learning, and robotics. Consider the future implications of machine learning, potential challenges, and ethical concerns. Discover how this technology is reshaping scientific and industrial possibilities while understanding its limitations and potential pitfalls.
Syllabus
Introduction
Facial Recognition
Image Classification
Intuition
Surveillance
Image Captioning
What is the future
Wrapping Machine Learning
Imitation Learning
Robotics
Serious
Challenges
What could go wrong
Taught by
Steve Brunton
Related Courses
Deep Learning For Visual ComputingIndian Institute of Technology, Kharagpur via Swayam Literacy Essentials: Core Concepts Generative Adversarial Network
Pluralsight Machine Learning & Deep Learning Projects
The AI University via YouTube Implement Image Captioning with Recurrent Neural Networks
Pluralsight VirTex- Learning Visual Representations from Textual Annotations
Yannic Kilcher via YouTube