zhangabner

zhangabner

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zhangabner's repositories

amazonaws-hackathon-2021

亚马逊云科技线上黑客松2021作品提交

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azure-devops-docs-samples

DevOps Pipelines sample projects to use in documentation articles

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benja

business card reader

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Clean-Code-Notes

My notes of Clean Code book

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cleanlab-tools

Miscellaneous code made available for purposes of education, reproducibility, and transparency

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databricks-tpc-di

Databricks Implementation of the TPC-DI Specification using Traditional Notebooks and/or Delta Live Tables

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datadm

DataDM is your private data assistant. Slide into your data's DMs

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dbdemos

Demos to implement your Databricks Lakehouse

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eeg-notebooks

A collection of classic EEG experiments implemented with Python and Jupyter notebooks

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gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

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gpt-engineer

Specify what you want it to build, the AI asks for clarification, and then builds it.

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MetaGPT

🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo

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modern-data-warehouse-dataops

DataOps for the Modern Data Warehouse on Microsoft Azure. https://aka.ms/mdw-dataops.

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muse-lsl

Python script to stream EEG data from the muse 2016 headset

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nyc-taxi

Data Engineering Project (Live Dashboard) and On-the-fly ML Prediction using Kafka, Spark, ElasticSearch and HDFS

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presidio

Context aware, pluggable and customizable data protection and anonymization SDK for text and images

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pyspark-ai

English SDK for Apache Spark

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pyspark-debug-test

pyspark-debug-test

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Synapse

Samples for Azure Synapse Analytics

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SynapseBuildValidations

Various build validation for when working with Azure Synapse Workspaces in DevOps

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tree-of-thought-llm

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

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tree-of-thoughts

Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%

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trl

Train transformer language models with reinforcement learning.

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trlx

A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)

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