Modeling Related Topics 
Analytics Vidhya
APRIL 18, 2024
Meta has unveiled its much-awaited Llama 3 model, marking a significant milestone in the field of open-source large language models (LLMs). This new model sets a new standard for LLMs with enhanced capabilities and a commitment to responsible development.
Analytics Vidhya
APRIL 24, 2024
Introduction In the world of machine learning, the trend toward smaller, more efficient models has grown significantly. These compact models are crucial for developers and researchers who need to run applications locally on devices with limited resources.
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Analytics Vidhya
APRIL 13, 2024
Introduction Machine learning models hold immense potential, but they need to be effectively integrated into real-world applications to unlock their true value. This is where model deployment and serving tools come into play. By […] The post Top 11 Model Deployment and Serving Tools appeared first on Analytics Vidhya.
Analytics Vidhya
APRIL 21, 2024
Mixtral 8x22B by Mistral AI Crushes Benchmarks in 4+ Languages The post Mistral’s New Model Crushes Benchmarks in 4+ Languages appeared first on Analytics Vidhya.
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Let’s explore how you can apply scenario modeling in supply chain network design. To build your supply chain’s agility and responsiveness, you need to look at scenarios more frequently instead of relying on a single plan.
Analytics Vidhya
APRIL 23, 2024
KissanAI has made waves in the agricultural sector with the introduction of Dhenu Llama 3, a cutting-edge AI model tailored specifically for farmers. Also Read: KissanAI Introduces Dhenu Vision LLMs for […] The post KissanAI Unveils Dhenu Llama 3: A Revolutionary Agricultural AI Model appeared first on Analytics Vidhya.
Analytics Vidhya
APRIL 19, 2024
Introduction The landscape of artificial intelligence has been dramatically reshaped over the past few years by the advent of Large Language Models (LLMs). At the forefront of this […] The post Meta Llama 3: Redefining Large Language Model Standards appeared first on Analytics Vidhya.
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In this article, we share best practices about modeling carbon costs in network design. Do you want to know the environmental impact of your supply chain and make sustainable decisions?
Speaker: Gertjan de Lange
If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. Experience how efficient you can be when you fit your model with actionable data. Don't let uncertainty drive your business.
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This report explores how the state of supply chain network design has changed – including how the tools, maturity models, and market demands are transforming the network design practice. Advanced analytics & Scenario Modeling. This report is useful if you are interested in: Exploring new network design insights and capabilities.
Advertiser: Data Robot
As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models.
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Modeling your base case. Modeling carbon costs. Scenario analysis and optimization defined. Creating a strategic digital twin (digital representation) of your supply chain network. Optimizing your supply chain based on costs and service levels. Dealing with multiple capacity constraints. Network design for risk and resilience.
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The guide includes a checklist, an assessment, industry-specific use cases, and a data & analytics maturity model and roadmap. Download this guide for practical advice on using a semantic layer to improve data literacy and scale self-service analytics.
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Answer 10 relevant questions and find out if your needs qualify for advanced network design & scenario modeling technology. Dedicated supply chain network design software is fuelled by intuitive scenario analysis capabilities on the front end and powerful mathematical optimization on the back end.
Advertiser: Data Robot
How to choose the appropriate fairness and bias metrics to prioritize for your machine learning models. How to successfully navigate the bias versus accuracy trade-off for final model selection and much more. Download this guide to find out: How to build an end-to-end process of identifying, investigating, and mitigating bias in AI.
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