Courses from 1000+ universities
Two years after its first major layoff round, Coursera announces another, impacting 10% of its workforce.
600 Free Google Certifications
Graphic Design
Data Analysis
Digital Marketing
El rol de la digitalización en la transición energética
First Step Korean
Supporting Successful Learning in Primary School
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore AI applications in healthcare, from cancer screening to genomics, addressing challenges like bias and model limitations for improved patient care and equitable outcomes.
Explore AI-driven 3D content creation, from synthesizing worlds to neural simulation. Learn cutting-edge techniques for generating, composing, and rendering 3D objects and scenes using deep learning.
Explore techniques to address dataset bias in deep learning, including adversarial domain alignment, pixel space alignment, and consistency enforcement for improved model generalization.
Explore deep learning techniques for information extraction using Conditional Probabilistic Context-Free Grammars. Learn about document parsing, schema representation, and handling noisy data in this advanced lecture.
Comprehensive exploration of AI bias and fairness, covering types, sources, and mitigation strategies. Examines interpretation-driven and data-driven biases, feature bias, and advanced debiasing techniques for ethical AI development.
Explore evidential deep learning and uncertainty estimation in neural networks, covering probabilistic learning, types of uncertainty, Bayesian methods, and practical applications.
Explore deep learning limitations and new frontiers, including expressivity, generalization, failure modes, uncertainty, adversarial attacks, and emerging areas like graph learning and AutoML.
Comprehensive exploration of deep reinforcement learning, covering Q-functions, policy gradients, and real-world applications like AlphaGo. Ideal for understanding RL fundamentals and advanced concepts.
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.
Comprehensive lecture on Recurrent Neural Networks, covering theory, implementation, and applications. Explores sequence modeling, LSTM, attention mechanisms, and practical examples in deep learning.
Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques for building effective models.
Explore machine learning applications in digitizing scent, from understanding olfactory processes to predicting odor descriptors using graph neural networks and interpreting molecular fragrance data.
Explore neural rendering techniques, from forward and inverse rendering to 3D data representations, with insights on RenderNet, neural point-based graphics, and HoloGAN in this comprehensive lecture.
Explore generalizable autonomy in robot manipulation through imitation learning, visuo-motor policies, and reinforcement learning techniques. Discover innovative approaches for achieving adaptable and efficient robotic systems.
Explore neurosymbolic AI, combining deep learning and symbolic reasoning to address limitations in current AI systems. Learn about out-of-distribution performance, adversarial examples, and advantages of hybrid approaches.
Get personalized course recommendations, track subjects and courses with reminders, and more.