Lecture
Cloud computing support for IoT
Related lectures (38)
Self-supervised Learning for Autonomous Vehicles
Explores self-supervised learning for autonomous vehicles, deriving labels from data itself and discussing its applications and challenges.
Adaptive Filtering: LMS Algorithm
Covers adaptive filtering using the LMS algorithm for immobile recording scenarios, focusing on practical implementation in MATLAB.
Machine Learning for Physicists/Chemists: Image Classification
Covers the fundamentals of machine learning for physicists and chemists, focusing on image classification tasks using artificial intelligence.
Neural Networks: Training and Activation
Explores neural networks, activation functions, backpropagation, and PyTorch implementation.
Neural Networks Optimization
Explores neural networks optimization, including backpropagation, batch normalization, weight initialization, and hyperparameter search strategies.
Autonomous Vehicles: Intelligence and Perception
Explores intelligence, perception, and AI applications in autonomous vehicles, emphasizing rational thinking and social intelligence.
Machine Learning FundamentalsMOOC: Humanitarian Action in the Digital Age
Covers fundamental principles, opportunities, and challenges in machine learning.
Machine Learning Fundamentals
Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.
Learning-aided Program Reasoning
Explores bug-finding, verification, and the use of learning-aided approaches in program reasoning, showcasing examples like the Heartbleed bug and differential Bayesian reasoning.
Acquiring Data for Learning
Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.