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Basics of Neural Networks - EfficientML.ai Lecture 2

Offered By: MIT HAN Lab via YouTube

Tags

Neural Networks Courses Artificial Intelligence Courses Machine Learning Courses Deep Learning Courses Gradient Descent Courses Optimization Algorithms Courses Activation Functions Courses Backpropagation Courses Loss Functions Courses

Course Description

Overview

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Dive into the fundamentals of neural networks in this comprehensive lecture from MIT's 6.5940 course. Explore key concepts and principles of neural network architecture, learning algorithms, and optimization techniques. Gain insights from Professor Song Han as he breaks down complex topics into accessible explanations. Learn about activation functions, backpropagation, gradient descent, and other essential components that form the backbone of modern machine learning. Ideal for students and professionals looking to deepen their understanding of neural networks and their applications in efficient machine learning.

Syllabus

EfficientML.ai Lecture 2 - Basics of Neural Networks (MIT 6.5940, Fall 2024)


Taught by

MIT HAN Lab

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