Awesome AI in Finance
Section: Research Tools · AI-powered collaborative environment for Research.
Entry
Appears in 4 awesome lists
AI-powered collaborative research environment. You can use it to get recommendations of articles based on reading history, simplify papers, find out what articles are trending, search articles by meaning (not just keywords), create and share folders of articles, see lists of articles from specific…
Section: Research Tools · AI-powered collaborative environment for Research.
Section: Miscellaneous Tools · AI-powered collaborative environment for research. Find relevant papers, create collections to manage bibliography, and summarize content — all in one place
Section: Tools · AI-powered collaborative research environment. You can use it to get recommendations of articles based on reading history, simplify papers, find out what articles are trending, search articles by meaning (not just keywords), create and share folders of articles, see lists of articles from specific…
Section: Editors · aggregates all papers from arXiv, medRxiv, bioRxiv, and chemRxiv with ability to highlight and leave notes.
Transpile trained ML models into other languages. sklearn-porter - Transpile trained scikit-learn estimators to C, Java, JavaScript and others. mlflow - Manage the machine learning lifecycle, including experimentation, reproducibility and deployment. skll - Command-line utilities to make it easier…
Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…
"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…
A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io
Build and share delightful machine learning apps, all in Python. The de facto standard for creating interactive ML demos with automatic UI generation from function signatures. Powers thousands of Hugging Face Spaces.
Workflow management system that makes it easy to take your data pipelines and add semantics like retries, logging, dynamic mapping, caching, failure notifications, and more.