Abhishek kumar
@uniabhi56
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AI/ML Engineer : Icelandic Startup & Part-Time Freelancer | 1+ yr building intelligent systems | Open for freelancing Collab
India
Joined December 2023
Day 31/150 #MLOpsLearning Containerized Vehicle Insurance model for cloud deployment! πβοΈ π§ Progress: β’ Built lightweight Docker image β’ Pushed to AWS ECR β’ Code synced to GitHub Model β Container β Cloud! π #MLOps #Docker #AWS #MachineLearning
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Day 31/150 #MLOpsLearning Containerized Vehicle Insurance model for cloud deployment! πβοΈ π§ Progress: β’ Built lightweight Docker image β’ Pushed to AWS ECR β’ Code synced to GitHub Model β Container β Cloud! π #MLOps #Docker #AWS #MachineLearning
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PEAK MALE CONTENTπ₯ As BCCI is not conducting any day night test matches, me and boys playing day night test match with pink ball π€©
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Day 30/150 #MLOpsLearning Deep dive into Data Version Control (DVC)! ππ π― Today's progress: β’ Created multiple data versions with DVC tracking β’ Explored version history using DVC Studio dashboard β’ Pushed experiment configs to GitHub for reproducibility. #code #Data
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Day 30/150 #MLOpsLearning Deep dive into Data Version Control (DVC)! ππ π― Today's progress: β’ Created multiple data versions with DVC tracking β’ Explored version history using DVC Studio dashboard β’ Pushed experiment configs to GitHub for reproducibility. #code #Data
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First day @Cloudflare β
Fixed a small config issue β
Everything is back to normal β
You're welcome, internet π #DevOps #HERO
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Day 29/150 #MLOpsLearning π DID DVC REVISION: β’ Revised DVC concepts through practical implementation β’ Created manual CSV dataset for hands-on learning β’ Tracked 3 different data versions with DVC β’ Full code pushed to GitHub π» Code: https://t.co/s8VefAVTFl
#pythoncode
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Day 29/150 #MLOpsLearning π DVC Revision today What I did: β’ Revised DVC concepts through practical implementation β’ Created manual CSV dataset for hands-on learning β’ Tracked 3 different data versions with DVC β’ Full code pushed to GitHub π» Code: https://t.co/s8VefAVTFl
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To the oncall SREs at Cloudflare and every app crying with themβ¦..
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ChatGPT, Claude, AND Twitter all throwing errors for 2+ hours? Anyone know what's going on with this Cloudflare situation? π #Twitter #ChatGPT #Claude #cloudflareconnect
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Day 28/150 #MLOpsLearning Develope Vehicle Insurance prediction model with FastAPI! ππ π§ Implementation highlights: β’ Built RESTful ML API using FastAPI β’ Created interactive web interface with HTML/CSS templates β’ Integrated web form for real-time predictions. #Python
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Day 28/150 #MLOpsLearning Develope Vehicle Insurance prediction model with FastAPI! ππ π§ Implementation highlights: β’ Built RESTful ML API using FastAPI β’ Created interactive web interface with HTML/CSS templates β’ Integrated web form for real-time predictions. #Python
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Day 27/150 #MLOpsLearning Built an automated model Pusher pipeline for Vehicle Insurance prediction! ππ - Uploads a trained model to the S3 bucket. - Auto-saves best performing model. - Production-ready model Pusher. - Cloud storage integration seamlessly. #code #ai #design
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Day 27/150 #MLOpsLearning Built an automated model Pusher pipeline for Vehicle Insurance prediction! ππ - Uploads a trained model to the S3 bucket. - Auto-saves best performing model. - Production-ready model Pusher. - Cloud storage integration seamlessly. #code #ai #design
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Day 26/150 #MLOpsLearning Built an automated model evaluation pipeline for Vehicle Insurance prediction! ππ β’ Compares new vs production models β’ Fetches current model from S3 β’ Evaluates model using F1 β’ Accepts model if significantly better #design #code #ai #data
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Day 26/150 #MLOpsLearning Built an automated model evaluation pipeline for Vehicle Insurance prediction! ππ β’ Compares new vs production models β’ Fetches current model from S3 β’ Evaluates model using F1 β’ Accepts model if significantly better #design #code #ai #data
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Day 25/150 #MLOpsLearning Built an automated model training pipeline for Vehicle Insurance prediction! ππ β’ Implemented Random Forest classifier with hyperparameter tuning β’ Automated data splitting & preprocessing β’ Comprehensive evaluation using classification metrics
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