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followers: 6.0 following: 26.0 repos: 64.0 gists: 0.0

Name: Corey Abshire

Type: User

Company: @databricks

Location: Minneapolis, MN

Hi there 👋

🔭 I’m currently working on ML 🤖 solutions for communications, media and entertainment (CME) 📡.
🌱 I’m currently learning the CME domain and Databricks field engineering practice.
👯 I’m looking to collaborate on any ML projects related to CME!
🤔 I’m looking for help with how to be a more effective and productive author and OSS contributor.
💬 Ask me about anything related to programming, system design, machine learning and data science.
📫 How to reach me: [email protected].
😄 Pronouns: He/Him
🙈 My personal GitHub account ➡ https://github.com/coreyabshire

Corey Abshire's Projects

chroma

the AI-native open-source embedding database

content-designing-applications-for-kubernetes

1082 - Designing Applications for Kubernetes, Will Boyd

content-github-actions-deep-dive-lab

Lab repository for Github Actions Deep Dive (1074)

content-github-actions-deep-dive-lesson

Lesson repository for Github Actions Deep Dive (1074)

databricks-gpu-serving-examples

Databricks GPU Model Serving Example Scripts

databricks-sql-clone

Python script to clone SQL dashboard from one workspace to another

dolly

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

dspy

DSPy: The framework for programming—not prompting—foundation models

eduktm

The Model Zoo of Knowledge Tracing Models

exelog

Enabling meticulous logging for your Spark Applications

giskard

🐢 Open-Source Evaluation & Testing for LLMs and ML models

gnn-db-blogpost

Code behind blog post deploying Graph Neural Networks (GNNs) for Monitoring Supply Chain Risk

gradio

Create UIs for your machine learning model in Python in 3 minutes

graphstorm

Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

kdd20-hands-on-tutorial

Scalable Graph Neural Networks with Deep Graph Library

kserve

Standardized Serverless ML Inference Platform on Kubernetes

langchain

⚡ Building applications with LLMs through composability ⚡

large-language-models

Notebooks for Large Language Models (LLMs) Specialization

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