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RLHF For High-Performance Decision-Making: Strategies and Optimization

Analytics Vidhya

It will be engineered to optimize decision-making and enhance performance in real-world complex systems. Introduction Reinforcement Learning from Human Factors/feedback (RLHF) is an emerging field that combines the principles of RL plus human feedback.

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4 Data-Driven Ways to Improve Employee Engagement

datapine

Also, a great way to collect employee engagement data is using Gallup’s Q12 survey , which consists of 12 carefully crafted questions that gauge the most crucial aspects of employee engagement. The results can later be displayed in an interactive HR report. Focus on employee feedback Employee feedback is a two-way street.

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Get Started With Interactive Weekly Reports For Performance Tracking

datapine

Businesses have been analyzing their performance for decades through traditional written reports, but with the amount of data being produced every day, the need for more frequent reporting is growing. This is where interactive weekly reports come into the picture. We will see these interactive reports in action throughout the post.

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Amazon OpenSearch Service Under the Hood : OpenSearch Optimized Instances(OR1)

AWS Big Data

Amazon OpenSearch Service recently introduced the OpenSearch Optimized Instance family (OR1), which delivers up to 30% price-performance improvement over existing memory optimized instances in internal benchmarks, and uses Amazon Simple Storage Service (Amazon S3) to provide 11 9s of durability.

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6 ways generative AI can optimize asset management

IBM Big Data Hub

Every asset manager, regardless of the organization’s size, faces similar mandates: streamline maintenance planning, enhance asset or equipment reliability and optimize workflows to improve quality and productivity. These foundation models, built on large language models, are trained on vast amounts of unstructured and external data.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.

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Top 5 Tools for Building an Interactive Analytics App

Smart Data Collective

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?