Vasilyeu

Vasilyeu's Stars

• microsoft/autogen

  A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour

  Language:Python40.5k4422.5k6k

• openai/swarm

  Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.

  Language:Python19k308112k

• microsoft/LightGBM

  A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

  Language:C++17k4353.5k3.9k

• evidentlyai/evidently

  Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

  Language:Jupyter Notebook5.8k46425634

• googlemaps/google-maps-services-python

  Python client library for Google Maps API Web Services

  Language:Python4.7k1892821.3k

• NVIDIA/nv-ingest

  NVIDIA Ingest is an early access set of microservices for parsing hundreds of thousands of complex, messy unstructured PDFs and other enterprise documents into metadata and text to embed into retrieval systems.

  Language:Python2.6k30144220

• DAGWorks-Inc/hamilton

  Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

  Language:Jupyter Notebook2k17341135

• chrismattmann/tika-python

  Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.

  Language:Python1.6k39285239

• WillKoehrsen/machine-learning-project-walkthrough

  An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!

  Language:Jupyter Notebook1.2k764565

• narwhals-dev/narwhals

  Lightweight and extensible compatibility layer between dataframe libraries!

  Language:Python85114520129

• NVlabs/GA3C

  Hybrid CPU/GPU implementation of the A3C algorithm for deep reinforcement learning.

  Language:Python6587236191

• doc-analysis/DocBank

  DocBank: A Benchmark Dataset for Document Layout Analysis

  Language:Python595205072

• datvodinh/rag-chatbot

  Chat with multiple PDFs locally

  Language:Python46911870

• jstockwin/py-pdf-parser

  A Python tool to help extracting information from structured PDFs.

  Language:Python39476943

• tonykipkemboi/ollama_pdf_rag

  A demo Jupyter Notebook showcasing a simple local RAG (Retrieval Augmented Generation) pipeline to chat with your PDFs.

  Language:Jupyter Notebook347926133

• joonspk-research/genagents

  Language:Python32213685

• venediktov/vanilla-rtb

  Real Time Bidding (RTB) - Demand Side Platform framework

  Language:C++321404384

• NVIDIA-AI-Blueprints/multimodal-pdf-data-extraction

  NVIDIA AI Blueprint for multimodal PDF data extraction for enterprise RAG

  3047036

• ispras/dedoc

  Dedoc is a library (service) for automate documents parsing and bringing to a uniform format. It automatically extracts content, logical structure, tables, and meta information from textual electronic documents. (Parse document; Document content extraction; Logical structure extraction; PDF parser; Scanned document parser; DOCX parser; HTML parser

  Language:Python214132424

• shiftsmartinc/orient-express

  A library to accelerate model deployments directly from colab notebooks

  Language:Python4100

• Vasilyeu/hedge-simulator

  Hedging simulations using put options

  Language:Python1100