yuminzhao91

yuminzhao91's Stars

• DataTalksClub/mlops-zoomcamp

  Free MLOps course from DataTalks.Club

  Language:Jupyter Notebook11.4k188932.2k

• aws/amazon-sagemaker-examples

  Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

  Language:Jupyter Notebook10.2k2691.4k6.8k

• graviraja/MLOps-Basics

  Language:Jupyter Notebook6.2k94211k

• data-science-on-aws/data-science-on-aws

  AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

  Language:Jupyter Notebook3.4k1192231.1k

• GokuMohandas/mlops-course

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook3k5419519

• OBenner/data-engineering-interview-questions

  More than 2000+ Data engineer interview questions.

  1.2k212437

• PacktPublishing/Data-Engineering-with-AWS

  Data Engineering with AWS, Published by Packt

  Language:Python318154209

• aws-samples/mlops-e2e

  MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK

  Language:TypeScript1336684

• PacktPublishing/Data-Engineering-with-AWS-2nd-edition

  Data Engineering with AWS, 2nd edition - Published by Packt

  Language:Python1234072

• Wittline/uber-expenses-tracking

  The goal of this project is to track the expenses of Uber Rides and Uber Eats through data Engineering processes using technologies such as Apache Airflow, AWS Redshift and Power BI.

  Language:Jupyter Notebook1187336

• thu-vu92/youtube-api-analysis

  Language:Jupyter Notebook1085538

• honghanhh/coursera-practical-data-science-specialization

  Solutions on Practical Data Science Specialization on Coursera (offered by deeplearning.ai)

  Language:Jupyter Notebook592247

• stanley-george-joseph/Customer-Analysis-Tableau

  This repository contains the data source and the tableau workbook used in my YouTube video: https://www.youtube.com/watch?v=_qReGTOrKTk

  412036

• aws-samples/aws-glue-cdk-cicd

  Build, Test and Deploy ETL solutions using AWS Glue and AWS CDK based CI/CD pipelines

  Language:Python394120

• razevedo1994/razv-data-engineering

  Portfolio of projects and studies conducted in data engineering.

  Language:Jupyter Notebook33243

• BrianKolowitz/data-focused-python

  Language:Jupyter Notebook323025

• moritzkoerber/covid-19-data-engineering-pipeline

  A Covid-19 data pipeline on AWS featuring PySpark/Glue, Docker, Great Expectations, Airflow, and Redshift, templated in CloudFormation and CDK, deployable via Github Actions.

  Language:Python23305

• im-nsk/Building-an-Automated-Weather-Data-Pipeline-with-Airflow-From-Ingestion-to-Data-Warehouse

  This project focuses on building a robust data pipeline using Apache Airflow to automate the ingestion of weather data from the OpenWeatherAPI and loading it into a data warehouse, specifically AWS Redshift.

  Language:Python21203

• Ashleshk/Practical-Data-Science-on-the-AWS-Cloud-Specialization

  @DeepLearning.AI Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It has helped me to develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker.

  Language:Jupyter Notebook202016

• ksdiwe/Youtube-Data-Scrapping-End-to-End-Project

  Language:Jupyter Notebook11101

• d-one/d-one-mlops-aws

  Repository for the D ONE MLOps AWS BlogPost

  Language:Jupyter Notebook102012

• akash-agni/Sagemaker_Notebooks

  Notebooks built and deployed in Sagemaker

  Language:Jupyter Notebook81012

• adimidania/deloitte-virtual-internship

  Submission for the STEM Virtual Program by Deloitte via Forage.

  Language:Python51013

• frankwwu/Machine-Learning-Engineering-for-Production-MLOps-Specialization

  Coursera Machine Learning Engineering for Production (MLOps) Specialization

  Language:Jupyter Notebook5302

• RamVegiraju/LinLearnerRegression

  End to end example of AWS SageMaker's in-built Linear Learner algorithm to solve regression problem.

  Language:Jupyter Notebook5103

• anair123/Building-a-Youtube-Data-Pipeline-With-AWS-and-Airflow

  Language:Python30

• SriramyaK/My-WiMLDS-Minneapolis-Talks

  Women in Machine Learning and Data science presentations and discussion materials

  Language:Jupyter Notebook2202

• abdallah-elsawy/Data-Engineering-Capstone-Project

  Today, 1% of the world is a barely livable hot zone. By 2070, that portion could go up to 19%.Billions of people call this land home. Where will they go? we will help the countries and governments to understand the basic relation between the climate change and the immigration issue. In this project we will use some important datasets related to immigration process and the temperature with the world. We will use some useful data engineering tools like data warehouses, AWS S3, Spark, Apache Airflow and AWS Warehouse like Redshift to deal with those datasets and try to indicates to the concerned people how the weather change and temperature is a important factor to the immigration process.

  Language:Jupyter Notebook1200

• bigoshunane/Big-Data-ETL-Pipeline-Project

  Google Colaboratory Notebook files to design ETL pipeline of Amazon music reviews and connection to AWS PostgreSQL database and analysis of the ratio of five star reviews as it relates to participation in the Vine program.

  Language:Jupyter Notebook1100

• mohammedar95/data_engineering

  several could computing and building different type of ETL and database infrastructures using python, SQL hosted in AWS

  Language:Jupyter Notebook1100