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Machine Learning Made Simple for Data Analysts with BigQuery ML

KDnuggets

Thanks to tools like BigQuery ML, you can harness the power of ML without needing a computer science degree. Let's explore how to get started.

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How to Choose Best ML Model for your Usecase?

Analytics Vidhya

Machine learning (ML) has become a cornerstone of modern technology, enabling businesses and researchers to make data-driven decisions with greater precision. However, with the vast number of ML models available, choosing the right one for your specific use case can be challenging. appeared first on Analytics Vidhya.

ML 290
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Best Practices for Building ETLs for ML

KDnuggets

It delves into several software engineering techniques and patterns applied to ML. This article talks about several best practices for writing ETLs for building training datasets.

ETL 377
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Complete Guide to Effortless ML Monitoring with Evidently.ai

Analytics Vidhya

Introduction Whether you’re a fresher or an experienced professional in the Data industry, did you know that ML models can experience up to a 20% performance drop in their first year? ML Monitoring aids in early […] The post Complete Guide to Effortless ML Monitoring with Evidently.ai

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations.

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Meta’s HawkEye: Transforming ML Debugging for Enhanced Efficiency

Analytics Vidhya

In a groundbreaking move, Meta has introduced HawkEye, a revolutionary toolkit aimed at transforming the landscape of machine learning (ML) debugging. Addressing the challenges of debugging at scale, HawkEye streamlines monitoring, observability, and debuggability for Meta’s ML-based products.

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Step-by-Step Guide to Deploying ML Models with Docker

KDnuggets

Learn how Docker can keep your ML models running smoothly, every time. Tired of fixing the same deployment issues?

ML 358
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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving. The number of use cases/corner cases that the system is expected to handle essentially explodes.