DUCKQUANT / THE QUANT & AI DIRECTORY
2,336 resources, ranked by in-directory PageRank
By DeepLearning.AI Welcome to Claude Code, the Highly Agentic Coding Assistant. This short course is built in partnership with Anthropics
By Vijay Janapa Reddi/Harvard University (2026) This textbook bridges the gap between theoretical foundations and practical engineering, emphasizing the…
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Explore this resource at its source website for documentation and current information.
Berkeley CS294/194-196 (2024) Introduction course on Large Language Model Agents. Includes Slides and Videos
Berkeley CS294/194-280 (2025) Advanced course on Large Language Model Agents. Includes Slides and Videos
MIT's introductory course on deep learning methods and applications.
By Christoph Molnar (2025) This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily…
TensorTonic interactive tutoring of Machine Learning theory and practice
Explore this resource at its source website for documentation and current information.
Dr. Valeriy Manokhin (PhD, MBA, CQF) — courses, books, and research on time series forecasting, conformal prediction, and machine learning. Author of Mastering Modern…
Applies deep reinforcement learning to high-dimensional stock portfolio trading problems.
Uses deep reinforcement learning to learn long-short portfolio allocation policies.
Reports on the FinRL contest series benchmarking data-driven financial reinforcement-learning agents.
Builds a Chinese fine-grained financial sentiment dataset and evaluates LLMs on it.
Retrieval-augmented generation improves LLM accuracy on financial sentiment classification.
Uses direct preference optimisation to align LLMs for sentiment-driven algorithmic trading.
Instruction-tunes general-purpose LLMs to perform financial sentiment analysis.
Combines multiple expert LLMs to produce trading decisions from heterogeneous data.
End-to-end tool-augmented agentic reinforcement-learning framework for stock trading.
LLM-agent framework combining fundamentals, news and macro signals for stock analysis.
Studies LLM-based stock trading behaviour inside simulated real-world market environments.
Bilingual Chinese-English benchmark for evaluating financial large language models.
Instruction-tunes a large language model on financial data to answer investment questions.
Applies deep reinforcement learning to continuous-action stock portfolio optimisation.
LLM-driven pipeline that automatically discovers and validates quantitative strategies.
Uses large language models with chain-of-thought to mine alpha factors in quant trading.
Adapts an open LLM to Dutch financial text and evaluates it on domain tasks.
Domain-adapted language model for sentiment extraction from bond-market text.
Uses ChatGPT-derived relation strengths to build a GNN for stock movement prediction.
A python bot that lets you trade in most crypto exchanges and allows you to optimize your strategies with machine learning.
Live leaderboard and benchmark dataset for evaluating AI-generated image detectors. Real-time rankings updated as new detectors are evaluated against 2,038…
Use the GitHub API to consume public events happening on GitHub
Weather intelligence APIs providing real-time and forecast weather data for business use.
Open global event database of news coverage with sentiment, geolocation and real-time updates.
Autonomous LLM Trading Asterism — a research-only multi-agent trading platform with evidence-first research, an auditable console, Shadow simulation and explici
