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Techbros Group
- Yogyakarta, Indonesia
- okta.fajar.suryani@gmail.com
- @oktafajar_
Stars
"RAG-Anything: All-in-One RAG Framework"
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
This repository contains the Hugging Face Agents Course.
Get your documents ready for gen AI
Production-ready platform for agentic workflow development.
Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
Kimi K2 is the large language model series developed by Moonshot AI team
A curated list of awesome deep vision web demo
Capture deep metrics on one or all assets within a Databricks workspace
This repository consists of code snippets explained on my medium blog for End-to-End ML Pipelines.
Tools for deploying Data Factory (v2) in Microsoft Azure
Databricks Azure DevOps Tutorial
Capturing model drift and handling its response - Example webinar
(Legacy) Command Line Interface for Databricks
Template for getting started with automated ML Ops on Azure Machine Learning
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Old scripts for one-off ST-to-E2 migrations. Use "terraform exporter" linked in the readme.
MLOps using Azure ML Services and Azure DevOps
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
A flexible and efficient deep neural network (DNN) compiler that generates high-performance executable from a DNN model description.
An Invitation to 3D Vision: A Tutorial for Everyone
An end-to-end implementation of intent prediction with Metaflow and other cool tools
A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.
The implementation of "End-to-End Multi-Task Learning with Attention" [CVPR 2019].