Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
SlideShare a Scribd company logo

201906 03 Introduction to NimbusML

•
•

NimbusML enables data scientists to use ML.NET to train models in Azure Machine Learning or anywhere else they use Python. NimbusML provides state-of-the-art ML algorithms, transforms and components, aiming to make them useful for all developers, data scientists, and information workers and helpful in all products, services and devices. The components are authored by the team members, as well as numerous contributors from MSR, CISL, Bing and other teams at Microsoft. NimbusML is interoperable with scikit-learn estimators and transforms, while adding a suite of highly optimized algorithms written in C++ and C# for speed and performance. The trained machine learning model can be used in a .NET application with ML.NET. This presentation will outline the features of NimbusML and provide a notebook-based demonstration using Azure Notebooks. This presentation is the third of four related to ML.NET and Automated ML. The presentation will be recorded with video posted to this YouTube Channel: http://bit.ly/2ZybKwI

1 of 20
Download to read offline
Introduction to Nimbus ML
Mark Tabladillo Ph.D. • Science doctorate from Georgia Tech • Analytics career based on SAS, Microsoft, open source • Tech Presentations: • Seattle, Portland, Chicago, Boston, Mountain View, San Francisco, San Antonio, Charlotte, Orlando • London, Hong Kong, Montreal • Social Media LinkedIn Twitter @marktabnet • Cloud Solution Architect • US CTO Customer Success
Microsoft Atlanta at Avalon
© Microsoft Corporation
Domain specific pretrained models To simplify solution development Azure Databricks Machine Learning VMs Popular frameworks To build advanced deep learning solutions TensorFlowPyTorch ONNX Azure Machine Learning LanguageSpeech … SearchVision Productive services To empower data science and development teams Powerful infrastructure To accelerate deep learning Scikit-Learn Familiar Data Science tools To simplify model development CPU GPU FPGA From the Intelligent Cloud to the Intelligent Edge Azure Notebooks JupyterVisual Studio Code Command line
Agenda About NimbusML Demos Action
About NimbusML • NimbusML provides state-of-the-art ML algorithms, transforms and components, aiming to make them useful for all developers, data scientists, and information workers and helpful in all products, services and devices. • The components are authored by the team members, as well as numerous contributors from MSR, CISL, Bing and other teams at Microsoft. • nimbusml is interoperable with scikit-learn estimators and transforms, while adding a suite of highly optimized algorithms written in C++ and C# for speed and performance.
NimbusML Features NimbusML trainers and transforms support the following data structures for the fit() and transform() methods: • numpy.ndarray • scipy.sparse_cst • pandas.DataFrame. NimbusML also supports streaming from files without loading the dataset into memory, which allows training on data significantly exceeding memory using FileDataStream. • With FileDataStream, NimbusML is able to handle up to billion features and billions of training examples for select algorithms
Demo https://github.com/ganik/NimbusML- Presentation
Demo https://github.com/Microsoft/NimbusML
Enterprise training and deployment
Training of Python scikit-learn models on Azure
Deploy Azure ML models at scale Azure Machine Learning Service
Model deployment
https://docs.microsoft.com/en-us/azure/architecture/reference-architectures/
Action
Nimbus ML Documentation https://docs.microsoft.com/en-us/NimbusML/overview
NimbusML on Github https://github.com/Microsoft/NimbusML
Gitter https://gitter.im/dotnet/mlnet
The Next Talk https://attendee.gotowebinar.com/register/4993774405253843981

More Related Content

201906 03 Introduction to NimbusML