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Experiment tracking with MLFlow.
Merges/Gathers and manages multiple web-server UIs into a simple single electron app listening on localhost or remote server(s). The initial aim of this electron app is to simplify DataScience/MachineLearning experiments by merging and managing all your web servers into a single app (e.g. tensorboard, jupyter notebook, MLFlow UI, NNI UI, etc.). …
The MLflow TensorFlow Guide is an educational project. This project demonstrates how to build, train, and manage a TensorFlow machine learning model using MLflow, a powerful open-source platform for the end-to-end machine learning lifecycle.
Host MLFlow Tracking Server and Model Registry as a containerized application on Kubernetes
🌐 Language identification for Scandinavian languages
In this project, you will create an end-to-end Airflow pipeline, integrated with MLflow, for CodePro, an EdTech startup, to perform lead scoring and maximize profitability while minimizing the Customer Acquisition Cost (CAC). The assignment involves data collection, preprocessing, and periodic model retraining within Airflow, alongside development
Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq
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