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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

It provides tools and components to facilitate end-to-end ML workflows, including data preprocessing, training, serving, and monitoring. Kubeflow integrates with popular ML frameworks, supports versioning and collaboration, and simplifies the deployment and management of ML pipelines on Kubernetes clusters.

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Maximize the Power of dbt and Snowflake to Achieve Efficient and Scalable Data Vault Solutions

phData

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Implement business rules and validations: Data Vault models often involve enforcing business rules and performing data quality checks.

SQL 52
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Top ETL Tools: Unveiling the Best Solutions for Data Integration

Pickl AI

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Introduction In today’s business landscape, data integration is vital. Read More: Advanced SQL Tips and Tricks for Data Analysts.

ETL 40
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Deployment of Machine Learning Models and its challenges

How to Learn Machine Learning

There is systematic process to analyze and respond to issues beyond deployment decision making; use Observational study to track potential model performance overtime, such as concept drift (declining accuracy of decision making and/or predictive power).

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Ask HN: Who wants to be hired? (July 2025)

Hacker News

I have about 3 YoE training PyTorch models on HPC clusters and 1 YoE optimizing PyTorch models, including with custom CUDA kernels. Ideal job would be designing, developing (CRDs, operators), monitoring and troubleshooting K8s clusters. Have performed multiple data migrations and pipeline development.

Python 63