Thinxtream IoT Services and Solutions Expertise Azure
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AZURE MACHINE LEARNING

Thinxtream has had a long partnership with Microsoft® and uses Azure® Machine Learning, Microsoft’s integrated, end-to-end data science and advanced analytics solution, with extensive support for industry standard open-source libraries and toolkits to develop intelligent IoT solutions.

  • Support for data ingestion from various Azure/Non-Azure data storage services
  • Advanced data preparation techniques like Filtering, Normalization, Principal Component Analysis, Partitioning and Sampling, etc.
  • Extend Azure Machine Learning model with R and Python™ Script modules
  • Making predictions with Elastic APIs like Request Response and Batch Execution Service
  • Model Visualizations with Scatterplots, Bar Charts, Box plots, Histograms, REPL with Jupyter™ Notebook
  • Retraining model, Cross validation and Parameter Sweeping
  • Support for wide range of data formats - ARFF, CSV, SVMLight, TSV, Excel®, ZIP
  • Integrating open source technologies like Scikit-learn, TensorFlow™, Microsoft Cognitive Toolkit (CNTK), Spark ML
  • Industry standard regression algorithms for training models, including Linear Regression, Deep Neural Networks, Decision Forest, Fast Forest Quantile, Ordinal Regression and Poisson Regression
  • Manage entire data science life cycle with cross-platform Desktop application - Azure Machine Learning Workbench
  • Deploy Azure Machine Learning models into wide variety of environments like local/on-prem devices, Docker images, IoT Edge devices, Azure Container Services (ACS)

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