Social And Emotional Learning Courses

SonoDoc: Case-based Learning in Bedside Ultrasound

Enhance bedside ultrasound skills through case-based learning. Improve patient care with rapid diagnosis, guided procedures, and integration into clinical practice. Ideal for various medical specialties.

• Independent
• On-Demand
• Free Online Course

Stanford Seminar - Representation Learning for Autonomous Robots, Anima Anandkumar

I will describe some key ingredients to enable this: (1) robust self-supervised learning (2) uncertainty awareness (3) compositionality. We utilize NVIDIA Isaac for GPU-accelerated robot learning at scale on a variety of tasks and domains.

• YouTube
• 56 minutes
• On-Demand
• Free Online Course

Deep Learning for Symbolic Mathematics - Guillaume Lample & Francois Charton

Explore deep learning applications in symbolic mathematics, covering integration techniques, ODEs, and model evaluation, with insights on generalization and comparisons to traditional methods.

• YouTube
• 53 minutes
• On-Demand
• Free Online Course

Stanford Seminar - Deep Learning for Medical Diagnoses

Explore deep learning's impact on medical diagnoses, from arrhythmia detection to chest X-ray interpretation, and its potential to revolutionize diagnostic access and decision support in healthcare.

• YouTube
• 57 minutes
• On-Demand
• Free Online Course

Stanford Seminar - Deep Learning in Speech Recognition

Explore deep learning's evolution and impact on speech recognition, from early AI to modern applications like Siri, covering key concepts, historical milestones, and practical implementations.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Online Course

Stanford Seminar - Enabling NLP, Machine Learning, and Few-Shot Learning Using Associative Processing

Explore associative processing for machine learning and NLP, enabling massive parallel data processing and in-memory computing for improved efficiency in various AI applications.

• YouTube
• 56 minutes
• On-Demand
• Free Online Course

Stanford CS229 - Machine Learning Full Course Taught by Andrew Ng - Autumn 2018

Comprehensive machine learning series covering fundamental concepts to advanced topics, taught by Andrew Ng. Includes algorithms, neural networks, and reinforcement learning.

• YouTube
• 1 day 3 hours
• On-Demand
• Free Online Course

Machine Learning with Graphs - Fall 2019

Comprehensive exploration of machine learning with graphs, covering network properties, community structures, graph neural networks, and their applications in various domains.

• YouTube
• 1 day 4 hours
• On-Demand
• Free Video

Stanford CS234: Reinforcement Learning - Winter 2019

Explore reinforcement learning fundamentals to advanced techniques, covering policy evaluation, deep Q-learning, imitation learning, policy gradients, fast RL, and Monte Carlo tree search.

• YouTube
• 19 hours
• On-Demand
• Free Online Course

Stanford CS330: Deep Multi-Task and Meta Learning

Explore advanced machine learning techniques for efficient learning across multiple tasks, including optimization-based meta-learning, Bayesian approaches, and reinforcement learning applications.

• YouTube
• 18 hours
• On-Demand
• Free Online Course

Stanford Seminar - Distributed Perception and Learning Between Robots and the Cloud

Explore distributed perception and learning in robotics, focusing on cloud-robot interactions, offloading strategies, and efficient data sampling for improved performance and cost reduction.

• YouTube
• 47 minutes
• On-Demand
• Free Online Course

Stanford Seminar - SMILE- Synchronized, Multi-sensory Integrated Learning Environment

Explore synchronized, multi-sensory integrated learning environments and their impact on distributed systems, cyber-physical networks, and innovative educational technologies.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Online Course

Fairness in Representation Learning - Natalie Dullerud

Explore fairness in deep metric learning, evaluating bias in representations and its impact on minority subgroups. Learn about a novel approach to mitigate bias and improve fairness in machine learning models.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Actionable Machine Learning for Tackling Distribution Shift - Huaxiu Yao

Explore techniques for building robust machine learning models that can handle distribution shifts, including subpopulation and domain shifts, and adapt to new test distributions with minimal labeled data.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Domain Adaptation with Invariant Representation Learning - What Transformations to Learn?

Explore domain adaptation in machine learning, focusing on invariant representation learning and its challenges. Learn about novel techniques for optimal feature mapping across domains.

• YouTube
• 58 minutes
• On-Demand
• Free Video