Managing your AI and Data assets in the enterprise - A hands-on workshop

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QU Fall school 2021 Speaker Series
The Machine Learning Exchange (MLX) is a Data and AI Assets Catalog and Execution Engine. It allows data scientists to browse, download and upload ML/AI pipelines, pipeline components, models, datasets and notebooks. With automated sample pipeline code generation, the registered components, models, datasets and notebooks can be run with Kubeflow Pipelines on Tekton on a Kubernetes cluster. Featured technologies include Kubernetes, Kubeflow, KServe, Datashim, Data Asset Exchange (DAX), Model Asset Exchange (MAX), and CodeNet.

In today's workshop, we will go over a scenario using CodeNet, a large scale code sample dataset, to demonstrate how to use MLX to manage and analyze datasets, to training and hosting ML models using the same platform.

We will go over how a data scientist can analyze a dataset, decide a model to train, and host it on the MLX platform. We will be using the CodeNet dataset which is a large scale code sample dataset to train a language classification model. Here are the dataset, notebook, and models we will be showing during the workshop.

Reference:
https://ml-exchange.org/datasets/codenet-langclass/
https://ml-exchange.org/notebooks/project-codenet-language-classification/
https://ml-exchange.org/models/codenet-language-classification
Category
Management
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