Social And Emotional Learning Courses

Nicholas Renotte

Custom Indicators for Reinforcement Learning Trading Tutorial - GME Python Trading PT2

Learn to create custom financial indicators for Python Reinforcement Learning trading bots. Calculate RSI, SMA, and OBV, integrate them into a trading environment, and train an RL model for improved stock trading performance.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Nicholas Renotte

Reinforcement Learning for Trading Tutorial - GME RL Python Trading

Learn to build a Python trading bot using reinforcement learning, focusing on Gamestop stock data. Covers environment setup, data loading, agent training, and performance evaluation.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Nicholas Renotte

Python Reinforcement Learning Tutorial for Beginners

Learn to create an OpenAI gym environment, train a reinforcement learning algorithm for the Lunar Lander problem, and use stable_baselines algorithms in Python. Practical guide with code examples and step-by-step instructions.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Nicholas Renotte

Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python

Learn to create and train custom reinforcement learning environments using OpenAI Gym and Python. Covers environment setup, DQN agent training, and practical implementation with Keras-RL.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Learning to Act by Watching Unlabeled Online Videos - Paper Explained

Exploring OpenAI's Video PreTraining for Minecraft: leveraging unlabeled gameplay footage to create an AI agent capable of complex tasks, including crafting a diamond pickaxe.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Transformer Memory as a Differentiable Search Index - Machine Learning Research Paper Explained

Explore a novel approach to information retrieval using a single Transformer model that encodes corpus information in its parameters, enabling direct query-to-document mapping without external indices.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Improving Intrinsic Exploration with Language Abstractions - Machine Learning Paper Explained

Explores using natural language to improve reinforcement learning agents' exploration in sparse-reward environments, demonstrating significant performance gains across challenging tasks in MiniGrid and MiniHack.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Memory-Assisted Prompt Editing to Improve GPT-3 After Deployment - Machine Learning Paper Explained

Explore adaptive methods to enhance GPT-3's performance post-deployment using memory-based prompts, improving accuracy without retraining the model. Learn about applications in fine-tuning and personalization.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Avoiding Catastrophe - Active Dendrites Enable Multi-Task Learning in Dynamic Environments

Explore how active dendrites in neural networks mitigate catastrophic forgetting, enabling multi-task learning and adaptation in dynamic environments through context-sensitive gating and sparse representations.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Author Interview - VOS- Learning What You Don't Know by Virtual Outlier Synthesis

Interview exploring Virtual Outlier Synthesis for out-of-distribution detection in neural networks. Discusses motivations, methodology, and key findings of novel approach to improve model robustness using synthesized outlier data.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Learning What You Don't Know by Virtual Outlier Synthesis - Paper Explained

Explore Virtual Outlier Synthesis, a novel method for improving out-of-distribution detection in deep learning models by generating synthetic outliers during training to enhance decision boundary regularization.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Spurious Normativity Enhances Learning of Compliance and Enforcement Behavior in Artificial Agents

Explore how arbitrary social norms enhance learning of rule enforcement in AI agents, with insights on societal implications and potential applications in artificial general intelligence.

• YouTube
• 1 hour 37 minutes
• Self-Paced
• Free Video

Yannic Kilcher

AI and Formal Math - Formal Mathematics Statement Curriculum Learning

Explore AI's potential in formal mathematics through expert iteration, curriculum learning, and language modeling. Discover how machines and humans can collaborate to solve complex mathematical problems.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Can Wikipedia Help Offline Reinforcement Learning - Author Interview

Exploring the potential of pre-trained language models in offline reinforcement learning, discussing experimental results, model performance, and future directions for leveraging sequence modeling techniques in RL tasks.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Can Wikipedia Help Offline Reinforcement Learning? - Paper Explained

Exploring how pre-training on Wikipedia improves offline reinforcement learning models, enhancing performance, reducing parameters, and revealing connections between language and RL domains.

• YouTube
• 39 minutes
• Self-Paced
• Free Video