On the Road to Artificial General Intelligence
Exploring the potential of game engines as virtual biodomes for AI evolution, showcasing advancements in reinforcement learning and the path towards Artificial General Intelligence.
A Code-Driven Introduction to Reinforcement Learning
Hands-on introduction to reinforcement learning, covering Markov decision processes and RL algorithms. Includes live coding of a GridWorld simulation and practical steps for industrial applications.
How to Leverage Reinforcement Learning
Explore reinforcement learning's key concepts, industry applications, and potential impact on business strategies. Gain insights into problem definition, interpretability challenges, and real-life implementations of RL algorithms.
Industrial Applications of Reinforcement Learning
Explore real-world applications of reinforcement learning in industry, from robotics to tech and transport. Learn to identify RL-suitable challenges and implement practical solutions.
The Road to General AI
Explore AI's evolution towards general intelligence through game implementations, reinforcement learning, and advanced techniques like multi-agent systems and hierarchical learning.
How to Leverage Reinforcement Learning
Explore reinforcement learning's key concepts, industry applications, and implementation challenges with experts Phil Winder and Rebecca Nugent. Gain insights on problem definition, getting started, and managing risks in RL projects.
Machine Learning for Autonomous Vehicles
Explore machine learning applications in autonomous vehicles, covering data requirements, security, language choices, and model deployment considerations with industry experts Oscar Beijbom and Prayson Daniel.
AutoFR - Automated Filter Rule Generation for Adblocking
Innovative reinforcement learning framework for automated ad-blocking filter rule creation, balancing ad removal and visual integrity while matching EasyList's effectiveness and offering scalability.
Speeding Up Innovation
Explore best practices in continuous delivery, cloud-native serverless applications, and chaos engineering to optimize time-to-value and ensure resilience in strategic workloads.
How to Create & Develop High-performing Data Science Teams
Insights on building effective data science teams: skill mix, culture, and value creation. Learn strategies for recruiting, developing, and embedding high-performing analytics teams in organizations.
Self-Supervised Learning - Towards Autonomously Learning Machines
Explore cutting-edge AI techniques for autonomous learning machines, focusing on self-supervised learning methods that reduce reliance on labeled data and enhance general understanding.
What We Need to Do to Continue Advancing Deep Learning
Explore advancements in deep learning, including reinforcement learning, generative adversarial networks, and neural networks, with insights on AI's future and its impact on various fields.
Bridging the Gap between QoE and QoS in Congestion Control - A Large-scale Mobile Web Service Perspective
Explore a novel approach to enhance mobile web services by bridging Quality of Experience and Quality of Service in congestion control, improving user experience through adaptive algorithms.
Decentralized Application-Level Adaptive Scheduling for Multi-Instance DNNs on Open Mobile Devices
Explores decentralized scheduling for multiple DNN-powered apps on open mobile systems, using Deep Reinforcement Learning to achieve balanced performance gains and energy savings across various scenarios.
AWARE - Automate Workload Autoscaling with Reinforcement Learning in Production Cloud Systems
Explore AWARE, an innovative framework using reinforcement learning for efficient workload autoscaling in cloud systems, offering faster adaptation and improved resource utilization.
Machine Learning Exposed - The Fundamentals
Gentle introduction to machine learning fundamentals, covering supervised, unsupervised, and reinforcement learning, with practical examples and intuitive explanations of underlying mathematics.
Using Deep Learning to Hunt Optical Counterparts to Gravitational Wave Events
Exploring deep learning applications in astrophysics to detect optical counterparts of gravitational waves, enhancing our understanding of cosmic events and advancing telescope scheduling techniques.
Hacking Reinforcement Learning
Explore innovative algorithms for generating high-quality samples in reinforcement learning environments, achieving superhuman performance with linear time complexity and good scalability.
Machine Learning for Everyone
Discover the essentials of machine learning, neural networks, and reinforcement learning in this engaging talk. Gain practical insights and witness a mind-blowing demo to kickstart your ML journey.
IoT and AI Software in Industry and Production
Explore the transformative potential of IoT data and AI in industry, focusing on Reinforcement Learning for industrial control tasks, from energy management to product quality optimization.
Reinforcement Learning and Minecraft - ML Con Spring 2018
Explore reinforcement learning through Minecraft's AI platform, Project Malmo. Learn to solve problems using deep learning techniques in a unique experimental environment.