Fascinating. The improvement may be greater than the report states. The abstract claims a 19% improvement, but isn’t 67.2% to 86.5% actually a 29% improvement (19 percentage points)?
MACHINE LEARNING
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Large Language Models as Foundational Technology for Future Applications
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There are these things called Large Language Models (LLMs) which are becoming the foundational capability on which everyone can build interesting applications – we are very early here, it is very exciting and the most talked about. LLMS..
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Data Science ML AI Analytics Resources Follow Guide
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End of this thread! If you are looking to learn more about
Data Science
ML/DL/AI
Analytics
Math & Statistics
Resources
MLOps Then, Don't forget to follow me at @avikumart_ for upcoming posts -
Full Lifecycle ML Model Automation and Real-Time Redeployment
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4) Automated deployment
5) Full lifecycle automation (Including retraining and redeployment of ML models in real-time) Learn more here https://
learn.microsoft.com/en-us/azure/ar
chitecture/example-scenario/mlops/mlops-maturity-model
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MLOps Maturity Model: Five Levels of Production Lifecycle
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2) MLOps maturity model There are 5 levels of the MLOps lifecycle in production 1) No MLOps (Static model deployment, used for POC)
2) DevOps but NO MLOps
3) Automated training (Cont…) -
ML Model Monitoring Performance Degradation Retraining
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– Monitoring Monitoring ML models in production is super important to track performance in real time. If the performance of models degrades it requires retraining and diagnosis to update the quality of ML models in production
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ML Pipeline Orchestration for Automated MLOps Deployment
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– Orchestration and ML pipelines This includes converting ML code in modular components to create a connected pipeline for smother deployment and maintenance Pipelines also enable automated training and deployment for the MLOps lifecycle
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ML Model Lifecycle: Experiment Tracking and Deployment
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1/ Course overview (Life cycle of ML models) – ML modeling and Experiment tracking:
This includes ML model training and trekking each and every experiment to compare different models & deploy best model
tracking includes model parameters, accuracy measures, & model versioning -
MLOps Zoomcamp Week 1: Introduction and Maturity Model
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Here's an update from week 1 of MLOps Zoomcamp by @DataTalksClub This week was about introduction to MLOps, setting up an environment, and the MLOps maturity model. A thread
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HuggingChat Adds Model Reply Labeling Feature Training
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New on HuggingChat: you can now label the model's replies with / This provides signal for further model training Try it out and let us know what you think! @huggingface